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64
64
category
stringclasses
1 value
turns
sequencelengths
1
1
ground_truth
stringlengths
2
3.05k
task
stringclasses
3 values
livebench_release_date
timestamp[s]
livebench_removal_date
stringclasses
1 value
e114ea800daa6938bd7bbc29c6fde32844324662764b5cb63d7e4e78c3b66c65
data_analysis
[ "Please convert the Input Table from CSV format to JSON format. Please respond only with the table. \n Input Table: swsLengthHR,swsTimeHR,swsLengthT,swsTimeT,decreasePercentageT,swsTimeM,swsLengthM,decreasePercentageM\n0.40387,0.125,0.08702,0.03448,0.6986,0.05263,-0.73889,0.74472\n0.0,0.0,0.0,0.0,0.68042,0.18421,0.21577,0.79564\n0.35725,0.125,0.17935,0.10345,0.75992,0.28947,1.02812,0.88919\n0.08659,0.04167,0.0,0.0,0.7441,0.0,-1.00196,0.61898\n0.33737,0.16667,0.12945,0.06897,0.64663,0.05263,-0.79333,0.62288\n0.05548,0.04167,0.11269,0.03448,0.7798,0.23684,1.20461,0.71585\n0.32591,0.58333,0.02467,0.03448,0.66134,0.55263,0.73997,0.53467\n0.0,0.0,0.03896,0.03448,0.66269,0.15789,2.84312,0.65916\n0.06369,0.04167,0.39228,0.13793,0.73069,0.18421,0.45976,0.67106\n0.0,0.0,0.43818,0.13793,0.68326,0.13158,-0.3926,0.81514\n0.0,0.0,0.0,0.0,0.67266,0.0,-1.00196,0.96306\n \n Output: \n" ]
{"69":{"swsLengthHR":0.40387,"swsTimeHR":0.125,"swsLengthT":0.08702,"swsTimeT":0.03448,"decreasePercentageT":0.6986,"swsTimeM":0.05263,"swsLengthM":-0.73889,"decreasePercentageM":0.74472},"88":{"swsLengthHR":0.0,"swsTimeHR":0.0,"swsLengthT":0.0,"swsTimeT":0.0,"decreasePercentageT":0.68042,"swsTimeM":0.18421,"swsLengthM":0.21577,"decreasePercentageM":0.79564},"73":{"swsLengthHR":0.35725,"swsTimeHR":0.125,"swsLengthT":0.17935,"swsTimeT":0.10345,"decreasePercentageT":0.75992,"swsTimeM":0.28947,"swsLengthM":1.02812,"decreasePercentageM":0.88919},"54":{"swsLengthHR":0.08659,"swsTimeHR":0.04167,"swsLengthT":0.0,"swsTimeT":0.0,"decreasePercentageT":0.7441,"swsTimeM":0.0,"swsLengthM":-1.00196,"decreasePercentageM":0.61898},"23":{"swsLengthHR":0.33737,"swsTimeHR":0.16667,"swsLengthT":0.12945,"swsTimeT":0.06897,"decreasePercentageT":0.64663,"swsTimeM":0.05263,"swsLengthM":-0.79333,"decreasePercentageM":0.62288},"201":{"swsLengthHR":0.05548,"swsTimeHR":0.04167,"swsLengthT":0.11269,"swsTimeT":0.03448,"decreasePercentageT":0.7798,"swsTimeM":0.23684,"swsLengthM":1.20461,"decreasePercentageM":0.71585},"211":{"swsLengthHR":0.32591,"swsTimeHR":0.58333,"swsLengthT":0.02467,"swsTimeT":0.03448,"decreasePercentageT":0.66134,"swsTimeM":0.55263,"swsLengthM":0.73997,"decreasePercentageM":0.53467},"198":{"swsLengthHR":0.0,"swsTimeHR":0.0,"swsLengthT":0.03896,"swsTimeT":0.03448,"decreasePercentageT":0.66269,"swsTimeM":0.15789,"swsLengthM":2.84312,"decreasePercentageM":0.65916},"35":{"swsLengthHR":0.06369,"swsTimeHR":0.04167,"swsLengthT":0.39228,"swsTimeT":0.13793,"decreasePercentageT":0.73069,"swsTimeM":0.18421,"swsLengthM":0.45976,"decreasePercentageM":0.67106},"79":{"swsLengthHR":0.0,"swsTimeHR":0.0,"swsLengthT":0.43818,"swsTimeT":0.13793,"decreasePercentageT":0.68326,"swsTimeM":0.13158,"swsLengthM":-0.3926,"decreasePercentageM":0.81514},"44":{"swsLengthHR":0.0,"swsTimeHR":0.0,"swsLengthT":0.0,"swsTimeT":0.0,"decreasePercentageT":0.67266,"swsTimeM":0.0,"swsLengthM":-1.00196,"decreasePercentageM":0.96306}}
tablereformat
2024-06-24T00:00:00
09752b3d3e355017282301de1735bd903221368e1fadf3e64aa9594ef7730e62
data_analysis
[ "Please convert the Input Table from HTML format to JSON format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>Country</th>\n <th>Inequality HDI</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>Indonesia</td>\n <td>2</td>\n </tr>\n <tr>\n <td>Azerbaijan</td>\n <td>1</td>\n </tr>\n <tr>\n <td>Denmark</td>\n <td>0</td>\n </tr>\n <tr>\n <td>North Macedonia</td>\n <td>2</td>\n </tr>\n <tr>\n <td>Canada</td>\n <td>0</td>\n </tr>\n <tr>\n <td>Palau</td>\n <td>2</td>\n </tr>\n <tr>\n <td>Papua New Guinea</td>\n <td>3</td>\n </tr>\n <tr>\n <td>Samoa</td>\n <td>2</td>\n </tr>\n <tr>\n <td>Marshall Islands</td>\n <td>2</td>\n </tr>\n <tr>\n <td>Lebanon</td>\n <td>2</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
{"111":{"Country":"Indonesia","Inequality HDI":2},"88":{"Country":"Azerbaijan","Inequality HDI":1},"4":{"Country":"Denmark","Inequality HDI":0},"83":{"Country":"North Macedonia","Inequality HDI":2},"17":{"Country":"Canada","Inequality HDI":0},"70":{"Country":"Palau","Inequality HDI":2},"153":{"Country":"Papua New Guinea","Inequality HDI":3},"115":{"Country":"Samoa","Inequality HDI":2},"101":{"Country":"Marshall Islands","Inequality HDI":2},"108":{"Country":"Lebanon","Inequality HDI":2}}
tablereformat
2024-06-24T00:00:00
eb8aebddc3e1eff35a92de9e8306dfcfebd25201eefda2921b830226b5347dc5
data_analysis
[ "Please convert the Input Table from HTML format to JSON format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>country</th>\n <th>code country</th>\n <th>Year</th>\n <th>Maize yield</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>Low-income countries</td>\n <td>0</td>\n <td>1993</td>\n <td>1.675.252</td>\n </tr>\n <tr>\n <td>Lebanon</td>\n <td>LBN</td>\n <td>1971</td>\n <td>82.339.996</td>\n </tr>\n <tr>\n <td>United Kingdom</td>\n <td>GBR</td>\n <td>1999</td>\n <td>0</td>\n </tr>\n <tr>\n <td>Small Island Develop</td>\n <td>0</td>\n <td>1972</td>\n <td>1.0519</td>\n </tr>\n <tr>\n <td>Cuba</td>\n <td>CUB</td>\n <td>1964</td>\n <td>9.474</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
{"6792":{"country":"Low-income countries","code country":"0","Year":1993,"Maize yield":"1.675.252"},"2266":{"country":"Lebanon","code country":"LBN","Year":1971,"Maize yield":"82.339.996"},"8256":{"country":"United Kingdom","code country":"GBR","Year":1999,"Maize yield":"0"},"2530":{"country":"Small Island Develop","code country":"0","Year":1972,"Maize yield":"1.0519"},"799":{"country":"Cuba","code country":"CUB","Year":1964,"Maize yield":"9.474"}}
tablereformat
2024-06-24T00:00:00
57772b38ab8d4f9f2e30d5e0cca6e007f228786523ed027bdbf37b59fe20e3b1
data_analysis
[ "Please convert the Input Table from TSV format to JSONL format. Please respond only with the table. \n Input Table: plan_strategy\trtpid\ttitle\tscope\topen_period\tfunding_millions_yoe\tcounty\nRegional Rail\t21-T11-107\tRail | Service Frequ\tThis program include\t2036 - 2050\t2840\tVarious\nRegional Rail\t21-T11-097\tFerry | Service Expa\tThis program include\t2021 - 2035\t271\tSan Francisco\nInterchanges and Bot\t21-T06-041\tCorridor & Interchan\tThis program include\t2021 - 2035\t40\tAlameda\nRegional Rail\t21-T11-101\tRail | Modernization\tThis program include\t2021 - 2035\t1980\tVarious\nRegional Rail\t21-T11-201\tRail | New Station |\tThis program include\t2021 - 2035\t14\tSonoma\nInterchanges and Bot\t21-T06-020\tCorridor & Interchan\tThis program include\t2021 - 2035\t173\tVarious\n \n Output: \n" ]
{"plan_strategy":"Regional Rail","rtpid":"21-T11-107","title":"Rail | Service Frequ","scope":"This program include","open_period":"2036 - 2050","funding_millions_yoe":2840,"county":"Various"} {"plan_strategy":"Regional Rail","rtpid":"21-T11-097","title":"Ferry | Service Expa","scope":"This program include","open_period":"2021 - 2035","funding_millions_yoe":271,"county":"San Francisco"} {"plan_strategy":"Interchanges and Bot","rtpid":"21-T06-041","title":"Corridor & Interchan","scope":"This program include","open_period":"2021 - 2035","funding_millions_yoe":40,"county":"Alameda"} {"plan_strategy":"Regional Rail","rtpid":"21-T11-101","title":"Rail | Modernization","scope":"This program include","open_period":"2021 - 2035","funding_millions_yoe":1980,"county":"Various"} {"plan_strategy":"Regional Rail","rtpid":"21-T11-201","title":"Rail | New Station |","scope":"This program include","open_period":"2021 - 2035","funding_millions_yoe":14,"county":"Sonoma"} {"plan_strategy":"Interchanges and Bot","rtpid":"21-T06-020","title":"Corridor & Interchan","scope":"This program include","open_period":"2021 - 2035","funding_millions_yoe":173,"county":"Various"}
tablereformat
2024-06-24T00:00:00
8b25c07592f100c7c61af45d3de6eec07f4996d0a211f613cc1e224db02bba4c
data_analysis
[ "Please convert the Input Table from JSONL format to JSON format. Please respond only with the table. \n Input Table: {\"Profanity\":\"tongue fucker\",\"Severity Rating\":2.4,\"Severity Description\":\"Strong\"}\n{\"Profanity\":\"arse-shagger\",\"Severity Rating\":2.4,\"Severity Description\":\"Strong\"}\n{\"Profanity\":\"s.o.b.s\",\"Severity Rating\":1.6,\"Severity Description\":\"Strong\"}\n{\"Profanity\":\"bollocktician\",\"Severity Rating\":1.4,\"Severity Description\":\"Mild\"}\n{\"Profanity\":\"d1ck\",\"Severity Rating\":1.0,\"Severity Description\":\"Mild\"}\n{\"Profanity\":\"goddamned\",\"Severity Rating\":1.8,\"Severity Description\":\"Strong\"}\n{\"Profanity\":\"shittydick\",\"Severity Rating\":2.0,\"Severity Description\":\"Strong\"}\n{\"Profanity\":\"groper\",\"Severity Rating\":1.4,\"Severity Description\":\"Mild\"}\n \n Output: \n" ]
{"14":{"Profanity":"tongue fucker","Severity Rating":2.4,"Severity Description":"Strong"},"1541":{"Profanity":"arse-shagger","Severity Rating":2.4,"Severity Description":"Strong"},"199":{"Profanity":"s.o.b.s","Severity Rating":1.6,"Severity Description":"Strong"},"1477":{"Profanity":"bollocktician","Severity Rating":1.4,"Severity Description":"Mild"},"1154":{"Profanity":"d1ck","Severity Rating":1.0,"Severity Description":"Mild"},"857":{"Profanity":"goddamned","Severity Rating":1.8,"Severity Description":"Strong"},"123":{"Profanity":"shittydick","Severity Rating":2.0,"Severity Description":"Strong"},"846":{"Profanity":"groper","Severity Rating":1.4,"Severity Description":"Mild"}}
tablereformat
2024-06-24T00:00:00
ce1fa8f673c3d33b3986e4f4f148ab1a11e42cd2b7f15390f0f4f2acb530a6e3
data_analysis
[ "Please convert the Input Table from TSV format to JSONL format. Please respond only with the table. \n Input Table: Calendar Year\tActive Duty\tFull-Time (est) Guard+Reserve\tSelected Reserve FTE\tTotal Military FTE\tTotal Deaths\tAccident \tHostile Action\n2008\t1402227\t73000\t207917\t1683144\t1440\t506.0\t352\n1988\t2121659\t72000\t115836\t2309495\t1819\t1080.0\t0\n1981\t2093032\t22000\t91719\t2206751\t2380\t1524.0\t0\n2003\t1423348\t66000\t243284\t1732632\t1399\t597.0\t312\n1984\t2138339\t55000\t104583\t2297922\t1999\t1293.0\t1\n2004\t1411287\t66000\t234629\t1711916\t1847\t605.0\t735\n1995\t1502343\t65000\t94585\t1661928\t1040\t538.0\t0\n1982\t2112609\t41000\t97458\t2251067\t2319\t1493.0\t0\n1994\t1581649\t65000\t99833\t1746482\t1075\t544.0\t0\n1980\t2050758\t22000\t86872\t2159630\t2392\t1556.0\t0\n1997\t1418773\t65000\t94609\t1578382\t817\t433.0\t0\n1999\t1367838\t65000\t93104\t1525942\t796\t439.0\t0\n \n Output: \n" ]
{"Calendar Year":2008,"Active Duty":1402227,"Full-Time (est) Guard+Reserve":73000,"Selected Reserve FTE":207917,"Total Military FTE":1683144,"Total Deaths":1440,"Accident ":506.0,"Hostile Action":352} {"Calendar Year":1988,"Active Duty":2121659,"Full-Time (est) Guard+Reserve":72000,"Selected Reserve FTE":115836,"Total Military FTE":2309495,"Total Deaths":1819,"Accident ":1080.0,"Hostile Action":0} {"Calendar Year":1981,"Active Duty":2093032,"Full-Time (est) Guard+Reserve":22000,"Selected Reserve FTE":91719,"Total Military FTE":2206751,"Total Deaths":2380,"Accident ":1524.0,"Hostile Action":0} {"Calendar Year":2003,"Active Duty":1423348,"Full-Time (est) Guard+Reserve":66000,"Selected Reserve FTE":243284,"Total Military FTE":1732632,"Total Deaths":1399,"Accident ":597.0,"Hostile Action":312} {"Calendar Year":1984,"Active Duty":2138339,"Full-Time (est) Guard+Reserve":55000,"Selected Reserve FTE":104583,"Total Military FTE":2297922,"Total Deaths":1999,"Accident ":1293.0,"Hostile Action":1} {"Calendar Year":2004,"Active Duty":1411287,"Full-Time (est) Guard+Reserve":66000,"Selected Reserve FTE":234629,"Total Military FTE":1711916,"Total Deaths":1847,"Accident ":605.0,"Hostile Action":735} {"Calendar Year":1995,"Active Duty":1502343,"Full-Time (est) Guard+Reserve":65000,"Selected Reserve FTE":94585,"Total Military FTE":1661928,"Total Deaths":1040,"Accident ":538.0,"Hostile Action":0} {"Calendar Year":1982,"Active Duty":2112609,"Full-Time (est) Guard+Reserve":41000,"Selected Reserve FTE":97458,"Total Military FTE":2251067,"Total Deaths":2319,"Accident ":1493.0,"Hostile Action":0} {"Calendar Year":1994,"Active Duty":1581649,"Full-Time (est) Guard+Reserve":65000,"Selected Reserve FTE":99833,"Total Military FTE":1746482,"Total Deaths":1075,"Accident ":544.0,"Hostile Action":0} {"Calendar Year":1980,"Active Duty":2050758,"Full-Time (est) Guard+Reserve":22000,"Selected Reserve FTE":86872,"Total Military FTE":2159630,"Total Deaths":2392,"Accident ":1556.0,"Hostile Action":0} {"Calendar Year":1997,"Active Duty":1418773,"Full-Time (est) Guard+Reserve":65000,"Selected Reserve FTE":94609,"Total Military FTE":1578382,"Total Deaths":817,"Accident ":433.0,"Hostile Action":0} {"Calendar Year":1999,"Active Duty":1367838,"Full-Time (est) Guard+Reserve":65000,"Selected Reserve FTE":93104,"Total Military FTE":1525942,"Total Deaths":796,"Accident ":439.0,"Hostile Action":0}
tablereformat
2024-06-24T00:00:00
56ace477670fa1527771dc1a4f2babac3b704f1c313b8981a53ce892f55b6c05
data_analysis
[ "Please convert the Input Table from TSV format to CSV format. Please respond only with the table. \n Input Table: species\tquantity\nLAKE TROUT\t2931\nKOKANEE\t716220\nGRAYLING ARCTIC\t84211\nSUNFISH BLUEGILL\t47840\nWIPER\t386460\nSUCKER JUNE\t80510\nTIGER TROUT\t401119\nRAINBOW\t3904196\nBROOK TROUT\t232058\nCUTTHROAT\t1506513\nCHUB\t34740\nALL TROUT\t1650\nBROWN TROUT\t245553\nGOLDEN TROUT\t4581\n \n Output: \n" ]
species,quantity LAKE TROUT,2931 KOKANEE,716220 GRAYLING ARCTIC,84211 SUNFISH BLUEGILL,47840 WIPER,386460 SUCKER JUNE,80510 TIGER TROUT,401119 RAINBOW,3904196 BROOK TROUT,232058 CUTTHROAT,1506513 CHUB,34740 ALL TROUT,1650 BROWN TROUT,245553 GOLDEN TROUT,4581
tablereformat
2024-06-24T00:00:00
3f9091ebb24ea69d1e9ad7a20e3a617f47548595e9b0b0a46a95061ec3e81740
data_analysis
[ "Please convert the Input Table from HTML format to TSV format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>license_description</th>\n <th>zip_code</th>\n <th>license_id</th>\n <th>location</th>\n <th>date_issued</th>\n <th>city</th>\n <th>ward_precinct</th>\n <th>address</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>Retail Food Establis</td>\n <td>60607</td>\n <td>2959264</td>\n <td>{'latitude': '41.885</td>\n <td>2024-04-16T00:00:00.</td>\n <td>CHICAGO</td>\n <td>27-1</td>\n <td>205-209 N PEORIA ST</td>\n </tr>\n <tr>\n <td>Pharmaceutical Repre</td>\n <td>60031</td>\n <td>2960784</td>\n <td>NaN</td>\n <td>2024-03-22T00:00:00.</td>\n <td>GURNEE</td>\n <td>NaN</td>\n <td>[REDACTED FOR PRIVAC</td>\n </tr>\n <tr>\n <td>Wholesale Food Estab</td>\n <td>60640</td>\n <td>2964234</td>\n <td>{'latitude': '41.964</td>\n <td>2024-04-16T00:00:00.</td>\n <td>CHICAGO</td>\n <td>47-36</td>\n <td>4527 N RAVENSWOOD AV</td>\n </tr>\n <tr>\n <td>Limited Business Lic</td>\n <td>60613</td>\n <td>2957581</td>\n <td>{'latitude': '41.955</td>\n <td>2024-04-19T00:00:00.</td>\n <td>CHICAGO</td>\n <td>46-10</td>\n <td>4025 N SHERIDAN RD 1</td>\n </tr>\n <tr>\n <td>Tavern</td>\n <td>60613</td>\n <td>2962989</td>\n <td>{'latitude': '41.949</td>\n <td>2024-04-16T00:00:00.</td>\n <td>CHICAGO</td>\n <td>44-32</td>\n <td>3714 N CLARK ST 1ST</td>\n </tr>\n <tr>\n <td>Pawnbroker</td>\n <td>60639</td>\n <td>2959235</td>\n <td>{'latitude': '41.931</td>\n <td>2024-03-18T00:00:00.</td>\n <td>CHICAGO</td>\n <td>31-40</td>\n <td>5401 - 5405 W DIVERS</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
license_description zip_code license_id location date_issued city ward_precinct address Retail Food Establis 60607 2959264 {'latitude': '41.885 2024-04-16T00:00:00. CHICAGO 27-1 205-209 N PEORIA ST Pharmaceutical Repre 60031 2960784 2024-03-22T00:00:00. GURNEE [REDACTED FOR PRIVAC Wholesale Food Estab 60640 2964234 {'latitude': '41.964 2024-04-16T00:00:00. CHICAGO 47-36 4527 N RAVENSWOOD AV Limited Business Lic 60613 2957581 {'latitude': '41.955 2024-04-19T00:00:00. CHICAGO 46-10 4025 N SHERIDAN RD 1 Tavern 60613 2962989 {'latitude': '41.949 2024-04-16T00:00:00. CHICAGO 44-32 3714 N CLARK ST 1ST Pawnbroker 60639 2959235 {'latitude': '41.931 2024-03-18T00:00:00. CHICAGO 31-40 5401 - 5405 W DIVERS
tablereformat
2024-06-24T00:00:00
35b3098f43e9129b80af5263066ffad973670da10a3bbc4d350fa88cea4d980f
data_analysis
[ "Please convert the Input Table from TSV format to CSV format. Please respond only with the table. \n Input Table: credentialnumber\tlastname\tfirstname\tmiddlename\tcredentialtype\tstatus\tbirthyear\tfirstissuedate\nNA00164281\tJones\tSusan\tMary\tNursing Assistant Re\tACTIVE\t1963.0\t20040426.0\nLP60805320\tOlson\tChristina\tMarie\tLicensed Practical N\tCLOSED\t1978.0\t\nES61380905\tHawks\tWilliam\tJonathan\tEmergency Medical Te\tCLOSED\t1997.0\t\nNC10102413\tBlount\tJoyce\tL\tNursing Assistant Ce\tEXPIRED\t1971.0\t20080206.0\nVA60030789\tGrubich\tAshley\tNichole\tPharmacy Technician \tACTIVE\t1989.0\t20080815.0\nOL61464825\tWyer\tKyle\tDavid\tOsteopathic Physicia\tACTIVE\t1990.0\t20230725.0\nCP60969079\tMullin\tTiffany\tAnn\tSubstance Use Disord\tACTIVE\t1967.0\t20200114.0\nCG61289229\tOrtiz\tNicole\tLynne\tCounselor Agency Aff\tPENDING\t1968.0\t\nMC61191565\tCapozzolo\tMerry\tAlexandra\tMental Health Counse\tSUPERSEDED\t1991.0\t20210628.0\n \n Output: \n" ]
credentialnumber,lastname,firstname,middlename,credentialtype,status,birthyear,firstissuedate NA00164281,Jones,Susan,Mary,Nursing Assistant Re,ACTIVE,1963.0,20040426.0 LP60805320,Olson,Christina,Marie,Licensed Practical N,CLOSED,1978.0, ES61380905,Hawks,William,Jonathan,Emergency Medical Te,CLOSED,1997.0, NC10102413,Blount,Joyce,L,Nursing Assistant Ce,EXPIRED,1971.0,20080206.0 VA60030789,Grubich,Ashley,Nichole,Pharmacy Technician ,ACTIVE,1989.0,20080815.0 OL61464825,Wyer,Kyle,David,Osteopathic Physicia,ACTIVE,1990.0,20230725.0 CP60969079,Mullin,Tiffany,Ann,Substance Use Disord,ACTIVE,1967.0,20200114.0 CG61289229,Ortiz,Nicole,Lynne,Counselor Agency Aff,PENDING,1968.0, MC61191565,Capozzolo,Merry,Alexandra,Mental Health Counse,SUPERSEDED,1991.0,20210628.0
tablereformat
2024-06-24T00:00:00
0cbc79763d1930cd7c78821f52cbb8c368eacbee9ea3b9bb9ece1e79167deb4a
data_analysis
[ "Please convert the Input Table from JSONL format to JSON format. Please respond only with the table. \n Input Table: {\"app_no\":6067396,\"type\":\"HDR\",\"app_date\":\"2024-02-05T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6070694,\"type\":\"HDR\",\"app_date\":\"2024-03-20T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Needed\",\"wav_course\":\"Needed\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6068735,\"type\":\"HDR\",\"app_date\":\"2024-02-22T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Needed\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6070320,\"type\":\"HDR\",\"app_date\":\"2024-03-14T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6071839,\"type\":\"HDR\",\"app_date\":\"2024-04-04T00:00:00.\",\"status\":\"Approved - License I\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6070328,\"type\":\"HDR\",\"app_date\":\"2024-03-14T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Needed\",\"wav_course\":\"Needed\",\"defensive_driving\":\"Needed\"}\n{\"app_no\":6070076,\"type\":\"HDR\",\"app_date\":\"2024-03-11T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Needed\"}\n{\"app_no\":6070287,\"type\":\"HDR\",\"app_date\":\"2024-03-14T00:00:00.\",\"status\":\"Approved - License I\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6070315,\"type\":\"HDR\",\"app_date\":\"2024-03-14T00:00:00.\",\"status\":\"Approved - License I\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6067471,\"type\":\"HDR\",\"app_date\":\"2024-02-06T00:00:00.\",\"status\":\"Approved - License I\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6071018,\"type\":\"HDR\",\"app_date\":\"2024-03-24T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Needed\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6069877,\"type\":\"HDR\",\"app_date\":\"2024-03-08T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6070400,\"type\":\"HDR\",\"app_date\":\"2024-03-16T00:00:00.\",\"status\":\"Incomplete\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n{\"app_no\":6067570,\"type\":\"HDR\",\"app_date\":\"2024-02-07T00:00:00.\",\"status\":\"Approved - License I\",\"fru_interview_scheduled\":\"Not Applicable\",\"drug_test\":\"Complete\",\"wav_course\":\"Complete\",\"defensive_driving\":\"Complete\"}\n \n Output: \n" ]
{"188":{"app_no":6067396,"type":"HDR","app_date":"2024-02-05T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"},"951":{"app_no":6070694,"type":"HDR","app_date":"2024-03-20T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Needed","wav_course":"Needed","defensive_driving":"Complete"},"650":{"app_no":6068735,"type":"HDR","app_date":"2024-02-22T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Needed","wav_course":"Complete","defensive_driving":"Complete"},"823":{"app_no":6070320,"type":"HDR","app_date":"2024-03-14T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"},"118":{"app_no":6071839,"type":"HDR","app_date":"2024-04-04T00:00:00.","status":"Approved - License I","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"},"62":{"app_no":6070328,"type":"HDR","app_date":"2024-03-14T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Needed","wav_course":"Needed","defensive_driving":"Needed"},"115":{"app_no":6070076,"type":"HDR","app_date":"2024-03-11T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Needed"},"549":{"app_no":6070287,"type":"HDR","app_date":"2024-03-14T00:00:00.","status":"Approved - License I","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"},"531":{"app_no":6070315,"type":"HDR","app_date":"2024-03-14T00:00:00.","status":"Approved - License I","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"},"495":{"app_no":6067471,"type":"HDR","app_date":"2024-02-06T00:00:00.","status":"Approved - License I","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"},"654":{"app_no":6071018,"type":"HDR","app_date":"2024-03-24T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Needed","wav_course":"Complete","defensive_driving":"Complete"},"908":{"app_no":6069877,"type":"HDR","app_date":"2024-03-08T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"},"720":{"app_no":6070400,"type":"HDR","app_date":"2024-03-16T00:00:00.","status":"Incomplete","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"},"874":{"app_no":6067570,"type":"HDR","app_date":"2024-02-07T00:00:00.","status":"Approved - License I","fru_interview_scheduled":"Not Applicable","drug_test":"Complete","wav_course":"Complete","defensive_driving":"Complete"}}
tablereformat
2024-06-24T00:00:00
2379e1e2586eacdf0c9ea0b9385f3c679ff72aa7e2a74fb741aa42018b4d78ea
data_analysis
[ "Please convert the Input Table from TSV format to HTML format. Please respond only with the table. \n Input Table: id\toriginal_text\trewritten_text\trewrite_prompt\n181\tTitle: The Growing P\tTitle: Exploring the\tThe key difference i\n237\tSarah was shopping f\tSarah was browsing f\tConvey a more lighth\n102\tHey Marcelle! Just w\tMarcelle, beware the\tEncourage practice a\n7\tThe ovary is an esse\tThe ovary, a mystica\tEmploy a whimsical, \n109\tMildred woke up feel\tMildred woke up feel\tRevise the text with\n301\tLee used the pruner \tRephrase: Lee tidied\tRephrase the text by\n330\tRebecca eagerly awai\tRebecca cautiously a\tReflect a more cauti\n38\tTitle: The Schnitzel\tTitle: The Schnitzel\tRevise the text in a\n351\tJoseph, a young boy \tIn a world where dre\tRevise the text with\n \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>id</th> <th>original_text</th> <th>rewritten_text</th> <th>rewrite_prompt</th> </tr> </thead> <tbody> <tr> <td>181</td> <td>Title: The Growing P</td> <td>Title: Exploring the</td> <td>The key difference i</td> </tr> <tr> <td>237</td> <td>Sarah was shopping f</td> <td>Sarah was browsing f</td> <td>Convey a more lighth</td> </tr> <tr> <td>102</td> <td>Hey Marcelle! Just w</td> <td>Marcelle, beware the</td> <td>Encourage practice a</td> </tr> <tr> <td>7</td> <td>The ovary is an esse</td> <td>The ovary, a mystica</td> <td>Employ a whimsical,</td> </tr> <tr> <td>109</td> <td>Mildred woke up feel</td> <td>Mildred woke up feel</td> <td>Revise the text with</td> </tr> <tr> <td>301</td> <td>Lee used the pruner</td> <td>Rephrase: Lee tidied</td> <td>Rephrase the text by</td> </tr> <tr> <td>330</td> <td>Rebecca eagerly awai</td> <td>Rebecca cautiously a</td> <td>Reflect a more cauti</td> </tr> <tr> <td>38</td> <td>Title: The Schnitzel</td> <td>Title: The Schnitzel</td> <td>Revise the text in a</td> </tr> <tr> <td>351</td> <td>Joseph, a young boy</td> <td>In a world where dre</td> <td>Revise the text with</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
23369207a1755bd3b7cea52155e7cbbd7ab1e2fa79015d1f8776111b8648f8ed
data_analysis
[ "Please convert the Input Table from JSON format to CSV format. Please respond only with the table. \n Input Table: {\"620\":{\"fecha_reporte_web\":\"2020-09-03 00:00:00\",\"id_de_caso\":640674,\"fecha_de_notificaci_n\":\"2020-08-21 00:00:00\",\"departamento\":5,\"departamento_nom\":\"ANTIOQUIA\",\"ciudad_municipio\":5001,\"ciudad_municipio_nom\":\"MEDELLIN\",\"edad\":62},\"664\":{\"fecha_reporte_web\":\"2020-09-03 00:00:00\",\"id_de_caso\":640639,\"fecha_de_notificaci_n\":\"2020-08-19 00:00:00\",\"departamento\":5,\"departamento_nom\":\"ANTIOQUIA\",\"ciudad_municipio\":5360,\"ciudad_municipio_nom\":\"ITAGUI\",\"edad\":19},\"381\":{\"fecha_reporte_web\":\"2020-07-09 00:00:00\",\"id_de_caso\":133383,\"fecha_de_notificaci_n\":\"2020-06-29 00:00:00\",\"departamento\":11,\"departamento_nom\":\"BOGOTA\",\"ciudad_municipio\":11001,\"ciudad_municipio_nom\":\"BOGOTA\",\"edad\":31},\"643\":{\"fecha_reporte_web\":\"2020-10-23 00:00:00\",\"id_de_caso\":993946,\"fecha_de_notificaci_n\":\"2020-10-20 00:00:00\",\"departamento\":17,\"departamento_nom\":\"CALDAS\",\"ciudad_municipio\":17001,\"ciudad_municipio_nom\":\"MANIZALES\",\"edad\":28},\"221\":{\"fecha_reporte_web\":\"2021-01-14 00:00:00\",\"id_de_caso\":1841877,\"fecha_de_notificaci_n\":\"2021-01-04 00:00:00\",\"departamento\":11,\"departamento_nom\":\"BOGOTA\",\"ciudad_municipio\":11001,\"ciudad_municipio_nom\":\"BOGOTA\",\"edad\":35},\"379\":{\"fecha_reporte_web\":\"2020-07-09 00:00:00\",\"id_de_caso\":133381,\"fecha_de_notificaci_n\":\"2020-07-01 00:00:00\",\"departamento\":11,\"departamento_nom\":\"BOGOTA\",\"ciudad_municipio\":11001,\"ciudad_municipio_nom\":\"BOGOTA\",\"edad\":50},\"771\":{\"fecha_reporte_web\":\"2020-06-25 00:00:00\",\"id_de_caso\":78503,\"fecha_de_notificaci_n\":\"2020-06-19 00:00:00\",\"departamento\":70,\"departamento_nom\":\"SUCRE\",\"ciudad_municipio\":70001,\"ciudad_municipio_nom\":\"SINCELEJO\",\"edad\":64},\"944\":{\"fecha_reporte_web\":\"2020-09-03 00:00:00\",\"id_de_caso\":640279,\"fecha_de_notificaci_n\":\"2020-08-14 00:00:00\",\"departamento\":5,\"departamento_nom\":\"ANTIOQUIA\",\"ciudad_municipio\":5088,\"ciudad_municipio_nom\":\"BELLO\",\"edad\":32},\"318\":{\"fecha_reporte_web\":\"2021-01-13 00:00:00\",\"id_de_caso\":1830859,\"fecha_de_notificaci_n\":\"2020-12-29 00:00:00\",\"departamento\":68,\"departamento_nom\":\"SANTANDER\",\"ciudad_municipio\":68001,\"ciudad_municipio_nom\":\"BUCARAMANGA\",\"edad\":51},\"871\":{\"fecha_reporte_web\":\"2020-07-18 00:00:00\",\"id_de_caso\":186772,\"fecha_de_notificaci_n\":\"2020-06-30 00:00:00\",\"departamento\":5,\"departamento_nom\":\"ANTIOQUIA\",\"ciudad_municipio\":5088,\"ciudad_municipio_nom\":\"BELLO\",\"edad\":23},\"843\":{\"fecha_reporte_web\":\"2021-01-07 00:00:00\",\"id_de_caso\":1734645,\"fecha_de_notificaci_n\":\"2021-01-04 00:00:00\",\"departamento\":76,\"departamento_nom\":\"VALLE\",\"ciudad_municipio\":76001,\"ciudad_municipio_nom\":\"CALI\",\"edad\":73}} \n Output: \n" ]
fecha_reporte_web,id_de_caso,fecha_de_notificaci_n,departamento,departamento_nom,ciudad_municipio,ciudad_municipio_nom,edad 2020-09-03 00:00:00,640674,2020-08-21 00:00:00,5,ANTIOQUIA,5001,MEDELLIN,62 2020-09-03 00:00:00,640639,2020-08-19 00:00:00,5,ANTIOQUIA,5360,ITAGUI,19 2020-07-09 00:00:00,133383,2020-06-29 00:00:00,11,BOGOTA,11001,BOGOTA,31 2020-10-23 00:00:00,993946,2020-10-20 00:00:00,17,CALDAS,17001,MANIZALES,28 2021-01-14 00:00:00,1841877,2021-01-04 00:00:00,11,BOGOTA,11001,BOGOTA,35 2020-07-09 00:00:00,133381,2020-07-01 00:00:00,11,BOGOTA,11001,BOGOTA,50 2020-06-25 00:00:00,78503,2020-06-19 00:00:00,70,SUCRE,70001,SINCELEJO,64 2020-09-03 00:00:00,640279,2020-08-14 00:00:00,5,ANTIOQUIA,5088,BELLO,32 2021-01-13 00:00:00,1830859,2020-12-29 00:00:00,68,SANTANDER,68001,BUCARAMANGA,51 2020-07-18 00:00:00,186772,2020-06-30 00:00:00,5,ANTIOQUIA,5088,BELLO,23 2021-01-07 00:00:00,1734645,2021-01-04 00:00:00,76,VALLE,76001,CALI,73
tablereformat
2024-06-24T00:00:00
9dd93740e50a0913119103c1212284600703756ff930d2a8fa46d3dc97912d96
data_analysis
[ "Please convert the Input Table from CSV format to TSV format. Please respond only with the table. \n Input Table: Age ,Gender,BMI,Fever,Nausea/Vomting,Headache ,Diarrhea ,Fatigue & generalized bone ache \n41,2,28,2,2,2,1,2\n61,2,32,2,2,2,1,1\n44,2,32,2,1,2,2,1\n50,2,25,2,2,2,2,1\n42,1,35,2,1,2,1,2\n61,1,24,1,2,1,2,1\n35,2,32,2,1,1,2,2\n45,2,24,1,2,1,2,2\n33,2,22,1,2,2,2,1\n51,1,28,1,1,1,2,1\n32,2,28,1,1,1,1,1\n38,1,25,2,2,2,2,2\n53,2,29,2,1,1,2,2\n50,1,27,2,2,1,1,1\n \n Output: \n" ]
Age Gender BMI Fever Nausea/Vomting Headache Diarrhea Fatigue & generalized bone ache 41 2 28 2 2 2 1 2 61 2 32 2 2 2 1 1 44 2 32 2 1 2 2 1 50 2 25 2 2 2 2 1 42 1 35 2 1 2 1 2 61 1 24 1 2 1 2 1 35 2 32 2 1 1 2 2 45 2 24 1 2 1 2 2 33 2 22 1 2 2 2 1 51 1 28 1 1 1 2 1 32 2 28 1 1 1 1 1 38 1 25 2 2 2 2 2 53 2 29 2 1 1 2 2 50 1 27 2 2 1 1 1
tablereformat
2024-06-24T00:00:00
8f3ca4d439a2167eda91a41deaecf48838405ce32967097d2ec7e931b1313cf4
data_analysis
[ "Please convert the Input Table from TSV format to CSV format. Please respond only with the table. \n Input Table: Unnamed: 0\tfecha\thora\tsistema\tbandera\tprecio\ttipo_moneda\torigen_dato\n21150\t2012-12-18\t6\tHU\t0\t35.0\t1\t6\n830180\t2017-06-19\t3\tPT\t1\t45.8\t1\t1\n285124\t2014-07-30\t7\tSE3\t1\t32.17\t1\t2\n906469\t2017-11-10\t14\tLT\t0\t36.9\t1\t2\n148609\t2013-10-22\t8\tNO5\t1\t39.57\t1\t2\n1311561\t2019-11-22\t3\tNO5\t0\t37.48\t1\t2\n281792\t2014-07-23\t17\tFI\t1\t46.84\t1\t2\n702672\t2016-10-20\t15\tSE3\t1\t43.22\t1\t2\n788303\t2017-03-31\t20\tFI\t1\t33.9\t1\t2\n214985\t2014-03-13\t2\tSE4\t0\t25.57\t1\t2\n900240\t2017-10-29\t19\tFR\t0\t59.58\t1\t1\n1413759\t2020-05-02\t18\tDK1\t1\t8.5\t1\t2\n996520\t2018-04-30\t4\tNO4\t1\t35.17\t1\t2\n \n Output: \n" ]
Unnamed: 0,fecha,hora,sistema,bandera,precio,tipo_moneda,origen_dato 21150,2012-12-18,6,HU,0,35.0,1,6 830180,2017-06-19,3,PT,1,45.8,1,1 285124,2014-07-30,7,SE3,1,32.17,1,2 906469,2017-11-10,14,LT,0,36.9,1,2 148609,2013-10-22,8,NO5,1,39.57,1,2 1311561,2019-11-22,3,NO5,0,37.48,1,2 281792,2014-07-23,17,FI,1,46.84,1,2 702672,2016-10-20,15,SE3,1,43.22,1,2 788303,2017-03-31,20,FI,1,33.9,1,2 214985,2014-03-13,2,SE4,0,25.57,1,2 900240,2017-10-29,19,FR,0,59.58,1,1 1413759,2020-05-02,18,DK1,1,8.5,1,2 996520,2018-04-30,4,NO4,1,35.17,1,2
tablereformat
2024-06-24T00:00:00
31b5500fbd88c9b6087f15229a84578b6863700ef5b4bf2c645d8927a4723a77
data_analysis
[ "Please convert the Input Table from TSV format to HTML format. Please respond only with the table. \n Input Table: name\tid\tnametype\trecclass\tmass (g)\tfall\tyear\treclat\nRamlat as Sahmah 307\t51908\tValid\tH4-6\t327.5\tFound\t2009.0\t20.52627\nHammadah al Hamra 20\t11685\tValid\tLL6\t386.0\tFound\t1997.0\t28.633\nElephant Moraine 909\t9395\tValid\tCM2\t1.2\tFound\t1990.0\t-76.2675\nMacKay Glacier 05241\t36380\tValid\tL5\t2.5\tFound\t2005.0\t\nWisconsin Range 9161\t24301\tValid\tL5\t1.5\tFound\t1991.0\t-86.48087\n \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>name</th> <th>id</th> <th>nametype</th> <th>recclass</th> <th>mass (g)</th> <th>fall</th> <th>year</th> <th>reclat</th> </tr> </thead> <tbody> <tr> <td>Ramlat as Sahmah 307</td> <td>51908</td> <td>Valid</td> <td>H4-6</td> <td>327.5</td> <td>Found</td> <td>2009.0</td> <td>20.52627</td> </tr> <tr> <td>Hammadah al Hamra 20</td> <td>11685</td> <td>Valid</td> <td>LL6</td> <td>386.0</td> <td>Found</td> <td>1997.0</td> <td>28.63300</td> </tr> <tr> <td>Elephant Moraine 909</td> <td>9395</td> <td>Valid</td> <td>CM2</td> <td>1.2</td> <td>Found</td> <td>1990.0</td> <td>-76.26750</td> </tr> <tr> <td>MacKay Glacier 05241</td> <td>36380</td> <td>Valid</td> <td>L5</td> <td>2.5</td> <td>Found</td> <td>2005.0</td> <td>NaN</td> </tr> <tr> <td>Wisconsin Range 9161</td> <td>24301</td> <td>Valid</td> <td>L5</td> <td>1.5</td> <td>Found</td> <td>1991.0</td> <td>-86.48087</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
9b8b3c1cdfbadc5d248114dcd74f7376fe3e24db964f3acb8d12159404199aac
data_analysis
[ "Please convert the Input Table from JSON format to HTML format. Please respond only with the table. \n Input Table: {\"137\":{\"res_geo_short\":\"Lake\",\"work_geo_short\":\"Colusa\",\"year\":2016,\"total\":25,\"drove_alone\":25,\"_2_person_carpool\":0,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"855\":{\"res_geo_short\":\"Napa\",\"work_geo_short\":\"Riverside\",\"year\":2016,\"total\":30,\"drove_alone\":4,\"_2_person_carpool\":15,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"456\":{\"res_geo_short\":\"Fresno\",\"work_geo_short\":\"Los Angeles\",\"year\":2016,\"total\":675,\"drove_alone\":420,\"_2_person_carpool\":95,\"_3_person_carpool\":75,\"_4_person_carpool\":0},\"207\":{\"res_geo_short\":\"Alameda\",\"work_geo_short\":\"El Dorado\",\"year\":2016,\"total\":25,\"drove_alone\":0,\"_2_person_carpool\":0,\"_3_person_carpool\":25,\"_4_person_carpool\":0},\"921\":{\"res_geo_short\":\"Trinity\",\"work_geo_short\":\"Sacramento\",\"year\":2016,\"total\":4,\"drove_alone\":4,\"_2_person_carpool\":0,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"788\":{\"res_geo_short\":\"Colusa\",\"work_geo_short\":\"Placer\",\"year\":2016,\"total\":45,\"drove_alone\":45,\"_2_person_carpool\":0,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"940\":{\"res_geo_short\":\"San Luis Obispo\",\"work_geo_short\":\"San Benito\",\"year\":2016,\"total\":15,\"drove_alone\":15,\"_2_person_carpool\":0,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"820\":{\"res_geo_short\":\"Sutter\",\"work_geo_short\":\"Placer\",\"year\":2016,\"total\":1475,\"drove_alone\":1105,\"_2_person_carpool\":120,\"_3_person_carpool\":95,\"_4_person_carpool\":45},\"881\":{\"res_geo_short\":\"El Dorado\",\"work_geo_short\":\"Sacramento\",\"year\":2016,\"total\":21690,\"drove_alone\":18355,\"_2_person_carpool\":2005,\"_3_person_carpool\":195,\"_4_person_carpool\":105},\"877\":{\"res_geo_short\":\"Butte\",\"work_geo_short\":\"Sacramento\",\"year\":2016,\"total\":630,\"drove_alone\":490,\"_2_person_carpool\":60,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"509\":{\"res_geo_short\":\"Riverside\",\"work_geo_short\":\"Madera\",\"year\":2016,\"total\":4,\"drove_alone\":4,\"_2_person_carpool\":0,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"477\":{\"res_geo_short\":\"Sacramento\",\"work_geo_short\":\"Los Angeles\",\"year\":2016,\"total\":500,\"drove_alone\":315,\"_2_person_carpool\":50,\"_3_person_carpool\":30,\"_4_person_carpool\":40}} \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>res_geo_short</th> <th>work_geo_short</th> <th>year</th> <th>total</th> <th>drove_alone</th> <th>_2_person_carpool</th> <th>_3_person_carpool</th> <th>_4_person_carpool</th> </tr> </thead> <tbody> <tr> <td>Lake</td> <td>Colusa</td> <td>2016</td> <td>25</td> <td>25</td> <td>0</td> <td>0</td> <td>0</td> </tr> <tr> <td>Napa</td> <td>Riverside</td> <td>2016</td> <td>30</td> <td>4</td> <td>15</td> <td>0</td> <td>0</td> </tr> <tr> <td>Fresno</td> <td>Los Angeles</td> <td>2016</td> <td>675</td> <td>420</td> <td>95</td> <td>75</td> <td>0</td> </tr> <tr> <td>Alameda</td> <td>El Dorado</td> <td>2016</td> <td>25</td> <td>0</td> <td>0</td> <td>25</td> <td>0</td> </tr> <tr> <td>Trinity</td> <td>Sacramento</td> <td>2016</td> <td>4</td> <td>4</td> <td>0</td> <td>0</td> <td>0</td> </tr> <tr> <td>Colusa</td> <td>Placer</td> <td>2016</td> <td>45</td> <td>45</td> <td>0</td> <td>0</td> <td>0</td> </tr> <tr> <td>San Luis Obispo</td> <td>San Benito</td> <td>2016</td> <td>15</td> <td>15</td> <td>0</td> <td>0</td> <td>0</td> </tr> <tr> <td>Sutter</td> <td>Placer</td> <td>2016</td> <td>1475</td> <td>1105</td> <td>120</td> <td>95</td> <td>45</td> </tr> <tr> <td>El Dorado</td> <td>Sacramento</td> <td>2016</td> <td>21690</td> <td>18355</td> <td>2005</td> <td>195</td> <td>105</td> </tr> <tr> <td>Butte</td> <td>Sacramento</td> <td>2016</td> <td>630</td> <td>490</td> <td>60</td> <td>0</td> <td>0</td> </tr> <tr> <td>Riverside</td> <td>Madera</td> <td>2016</td> <td>4</td> <td>4</td> <td>0</td> <td>0</td> <td>0</td> </tr> <tr> <td>Sacramento</td> <td>Los Angeles</td> <td>2016</td> <td>500</td> <td>315</td> <td>50</td> <td>30</td> <td>40</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
1f592e4e1a40499fb15905f6badb7c507a643106aec8d907f34de9cd200cb3fa
data_analysis
[ "Please convert the Input Table from HTML format to TSV format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>Areas</th>\n <th>freq_1</th>\n <th>freq_2</th>\n <th>freq_3</th>\n <th>freq_4</th>\n <th>freq_5</th>\n <th>freq_6</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>21.011988</td>\n <td>1.0</td>\n <td>0.500439</td>\n <td>0.251738</td>\n <td>0.078005</td>\n <td>0.093293</td>\n <td>0.018903</td>\n </tr>\n <tr>\n <td>10.337971</td>\n <td>1.0</td>\n <td>0.466725</td>\n <td>0.419106</td>\n <td>0.274681</td>\n <td>0.267607</td>\n <td>0.157107</td>\n </tr>\n <tr>\n <td>10.849468</td>\n <td>1.0</td>\n <td>0.202631</td>\n <td>0.085090</td>\n <td>0.045319</td>\n <td>0.033782</td>\n <td>0.024511</td>\n </tr>\n <tr>\n <td>0.000000</td>\n <td>0.0</td>\n <td>0.000000</td>\n <td>0.000000</td>\n <td>0.000000</td>\n <td>0.000000</td>\n <td>0.000000</td>\n </tr>\n <tr>\n <td>0.000000</td>\n <td>0.0</td>\n <td>0.000000</td>\n <td>0.000000</td>\n <td>0.000000</td>\n <td>0.000000</td>\n <td>0.000000</td>\n </tr>\n <tr>\n <td>32.851421</td>\n <td>1.0</td>\n <td>0.254474</td>\n <td>0.120420</td>\n <td>0.074471</td>\n <td>0.045632</td>\n <td>0.031202</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
Areas freq_1 freq_2 freq_3 freq_4 freq_5 freq_6 21.011987996801384 1.0 0.5004387263728519 0.2517378735892901 0.078005199375179 0.093293367604831 0.0189026940475218 10.337970555779648 1.0 0.4667245036083286 0.4191063338191223 0.2746805132472518 0.2676071164217446 0.1571065760449514 10.84946821575966 1.0 0.2026312336424063 0.0850897545416327 0.0453185688575391 0.0337823596808117 0.0245107766664011 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 32.85142142890733 1.0 0.2544744562396613 0.1204201767574232 0.0744708623829048 0.0456319411571197 0.031201680845393
tablereformat
2024-06-24T00:00:00
e852443f6993386ec44106f68bee0f7f278cfd9fb116228e55a50713257692b2
data_analysis
[ "Please convert the Input Table from JSONL format to TSV format. Please respond only with the table. \n Input Table: {\"Outlook\":\"Rain\",\"Temperature\":\"Cool\",\"Humidity\":\"Normal\",\"Wind\":\"Weak\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Overcast\",\"Temperature\":\"Cool\",\"Humidity\":\"Normal\",\"Wind\":\"Weak\",\"Play_Badminton\":\"Yes\"}\n{\"Outlook\":\"Sunny\",\"Temperature\":\"Mild\",\"Humidity\":\"Normal\",\"Wind\":\"Strong\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Rain\",\"Temperature\":\"Mild\",\"Humidity\":\"High\",\"Wind\":\"Strong\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Overcast\",\"Temperature\":\"Mild\",\"Humidity\":\"High\",\"Wind\":\"Weak\",\"Play_Badminton\":\"Yes\"}\n{\"Outlook\":\"Rain\",\"Temperature\":\"Cool\",\"Humidity\":\"Normal\",\"Wind\":\"Strong\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Rain\",\"Temperature\":\"Cool\",\"Humidity\":\"High\",\"Wind\":\"Weak\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Overcast\",\"Temperature\":\"Hot\",\"Humidity\":\"High\",\"Wind\":\"Strong\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Overcast\",\"Temperature\":\"Hot\",\"Humidity\":\"High\",\"Wind\":\"Weak\",\"Play_Badminton\":\"Yes\"}\n{\"Outlook\":\"Rain\",\"Temperature\":\"Hot\",\"Humidity\":\"High\",\"Wind\":\"Strong\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Rain\",\"Temperature\":\"Cool\",\"Humidity\":\"High\",\"Wind\":\"Strong\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Sunny\",\"Temperature\":\"Hot\",\"Humidity\":\"High\",\"Wind\":\"Strong\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Rain\",\"Temperature\":\"Mild\",\"Humidity\":\"Normal\",\"Wind\":\"Weak\",\"Play_Badminton\":\"No\"}\n{\"Outlook\":\"Rain\",\"Temperature\":\"Hot\",\"Humidity\":\"Normal\",\"Wind\":\"Weak\",\"Play_Badminton\":\"No\"}\n \n Output: \n" ]
Outlook Temperature Humidity Wind Play_Badminton Rain Cool Normal Weak No Overcast Cool Normal Weak Yes Sunny Mild Normal Strong No Rain Mild High Strong No Overcast Mild High Weak Yes Rain Cool Normal Strong No Rain Cool High Weak No Overcast Hot High Strong No Overcast Hot High Weak Yes Rain Hot High Strong No Rain Cool High Strong No Sunny Hot High Strong No Rain Mild Normal Weak No Rain Hot Normal Weak No
tablereformat
2024-06-24T00:00:00
f44bcc507aa7a438c07f435c70e687868c07af785cc257410780ff861c54c646
data_analysis
[ "Please convert the Input Table from JSONL format to JSON format. Please respond only with the table. \n Input Table: {\"name\":\"Roosevelt County 050\",\"id\":22705,\"nametype\":\"Valid\",\"recclass\":\"L4\",\"mass (g)\":13.1,\"fall\":\"Found\",\"year\":1971.0,\"reclat\":34.08333}\n{\"name\":\"Asuka 881632\",\"id\":4341,\"nametype\":\"Valid\",\"recclass\":\"CO3\",\"mass (g)\":138.11,\"fall\":\"Found\",\"year\":1988.0,\"reclat\":-72.0}\n{\"name\":\"Asuka 87345\",\"id\":2702,\"nametype\":\"Valid\",\"recclass\":\"H4\",\"mass (g)\":73.78,\"fall\":\"Found\",\"year\":1987.0,\"reclat\":-72.0}\n{\"name\":\"Queen Alexandra Rang\",\"id\":19882,\"nametype\":\"Valid\",\"recclass\":\"L6\",\"mass (g)\":71.8,\"fall\":\"Found\",\"year\":1994.0,\"reclat\":-84.0}\n{\"name\":\"Northwest Africa 827\",\"id\":17856,\"nametype\":\"Valid\",\"recclass\":\"H3.9\",\"mass (g)\":48.7,\"fall\":\"Found\",\"year\":2000.0,\"reclat\":null}\n \n Output: \n" ]
{"36341":{"name":"Roosevelt County 050","id":22705,"nametype":"Valid","recclass":"L4","mass (g)":13.1,"fall":"Found","year":1971.0,"reclat":34.08333},"4568":{"name":"Asuka 881632","id":4341,"nametype":"Valid","recclass":"CO3","mass (g)":138.11,"fall":"Found","year":1988.0,"reclat":-72.0},"3707":{"name":"Asuka 87345","id":2702,"nametype":"Valid","recclass":"H4","mass (g)":73.78,"fall":"Found","year":1987.0,"reclat":-72.0},"33052":{"name":"Queen Alexandra Rang","id":19882,"nametype":"Valid","recclass":"L6","mass (g)":71.8,"fall":"Found","year":1994.0,"reclat":-84.0},"30803":{"name":"Northwest Africa 827","id":17856,"nametype":"Valid","recclass":"H3.9","mass (g)":48.7,"fall":"Found","year":2000.0,"reclat":null}}
tablereformat
2024-06-24T00:00:00
0bedfad80bcaab18b0ab15531247a61a8b75f42c6e87c40f05d398dc25984d35
data_analysis
[ "Please convert the Input Table from TSV format to CSV format. Please respond only with the table. \n Input Table: longitude\tlatitude\tstart_date\tend_date\tsource\thorizon_lower\thorizon_upper\taluminium_extractable\n34.32938\t-24.17005\t01/01/2008\t31/12/2018\tafsis_spectral\t20\t0\t392.113\n31.84637\t-8.19007\t01/01/2008\t31/12/2018\tafsis_spectral\t50\t20\t1148.256\n37.44746\t-5.31403\t01/01/2008\t31/12/2018\tafsis_spectral\t50\t20\t967.844\n37.08281\t-6.91857\t01/01/2008\t31/12/2018\tafsis_spectral\t50\t20\t999.199\n33.01138\t-3.06592\t01/01/2008\t31/12/2018\tafsis_spectral\t50\t20\t586.904\n-7.81056\t14.83462\t01/01/2008\t31/12/2018\tafsis_spectral\t50\t20\t550.305\n-2.40365\t6.98108\t01/01/2008\t31/12/2018\tafsis_spectral\t50\t20\t704.25\n35.36507\t-7.94579\t01/01/2008\t31/12/2018\tafsis_spectral\t50\t20\t904.558\n7.69961\t11.55999\t01/01/2008\t31/12/2018\tafsis_wetchem\t20\t0\t578.975\n31.22275\t-7.85177\t01/01/2008\t31/12/2018\tafsis_spectral\t20\t0\t745.065\n-13.42865\t10.53617\t01/01/2008\t31/12/2018\tafsis_spectral\t20\t0\t1861.265\n32.18869\t-2.47482\t01/01/2008\t31/12/2018\tafsis_spectral\t50\t20\t566.69\n \n Output: \n" ]
longitude,latitude,start_date,end_date,source,horizon_lower,horizon_upper,aluminium_extractable 34.32938,-24.17005,01/01/2008,31/12/2018,afsis_spectral,20,0,392.113 31.84637,-8.19007,01/01/2008,31/12/2018,afsis_spectral,50,20,1148.256 37.44746,-5.31403,01/01/2008,31/12/2018,afsis_spectral,50,20,967.844 37.08281,-6.91857,01/01/2008,31/12/2018,afsis_spectral,50,20,999.199 33.01138,-3.06592,01/01/2008,31/12/2018,afsis_spectral,50,20,586.904 -7.81056,14.83462,01/01/2008,31/12/2018,afsis_spectral,50,20,550.305 -2.40365,6.98108,01/01/2008,31/12/2018,afsis_spectral,50,20,704.25 35.36507,-7.94579,01/01/2008,31/12/2018,afsis_spectral,50,20,904.558 7.69961,11.55999,01/01/2008,31/12/2018,afsis_wetchem,20,0,578.975 31.22275,-7.85177,01/01/2008,31/12/2018,afsis_spectral,20,0,745.065 -13.42865,10.53617,01/01/2008,31/12/2018,afsis_spectral,20,0,1861.265 32.18869,-2.47482,01/01/2008,31/12/2018,afsis_spectral,50,20,566.69
tablereformat
2024-06-24T00:00:00
9cd37119651a821e2695ee073ddf004d50d9add830f4e7f3bc469f9b0d4ddbe3
data_analysis
[ "Please convert the Input Table from JSON format to HTML format. Please respond only with the table. \n Input Table: {\"963\":{\"fecha_reporte_web\":\"2020-09-03 00:00:00\",\"id_de_caso\":640218,\"fecha_de_notificaci_n\":\"2020-08-10 00:00:00\",\"departamento\":5,\"departamento_nom\":\"ANTIOQUIA\",\"ciudad_municipio\":5631,\"ciudad_municipio_nom\":\"SABANETA\",\"edad\":53},\"777\":{\"fecha_reporte_web\":\"2020-06-25 00:00:00\",\"id_de_caso\":78509,\"fecha_de_notificaci_n\":\"2020-06-19 00:00:00\",\"departamento\":70,\"departamento_nom\":\"SUCRE\",\"ciudad_municipio\":70001,\"ciudad_municipio_nom\":\"SINCELEJO\",\"edad\":31},\"495\":{\"fecha_reporte_web\":\"2020-07-18 00:00:00\",\"id_de_caso\":186899,\"fecha_de_notificaci_n\":\"2020-06-30 00:00:00\",\"departamento\":13001,\"departamento_nom\":\"CARTAGENA\",\"ciudad_municipio\":13001,\"ciudad_municipio_nom\":\"CARTAGENA\",\"edad\":62},\"618\":{\"fecha_reporte_web\":\"2020-09-03 00:00:00\",\"id_de_caso\":640672,\"fecha_de_notificaci_n\":\"2020-08-21 00:00:00\",\"departamento\":5,\"departamento_nom\":\"ANTIOQUIA\",\"ciudad_municipio\":5088,\"ciudad_municipio_nom\":\"BELLO\",\"edad\":67},\"331\":{\"fecha_reporte_web\":\"2020-07-18 00:00:00\",\"id_de_caso\":186936,\"fecha_de_notificaci_n\":\"2020-06-29 00:00:00\",\"departamento\":47001,\"departamento_nom\":\"STA MARTA D.E.\",\"ciudad_municipio\":47001,\"ciudad_municipio_nom\":\"SANTA MARTA\",\"edad\":48},\"220\":{\"fecha_reporte_web\":\"2021-01-14 00:00:00\",\"id_de_caso\":1841876,\"fecha_de_notificaci_n\":\"2021-01-12 00:00:00\",\"departamento\":11,\"departamento_nom\":\"BOGOTA\",\"ciudad_municipio\":11001,\"ciudad_municipio_nom\":\"BOGOTA\",\"edad\":34},\"497\":{\"fecha_reporte_web\":\"2020-07-18 00:00:00\",\"id_de_caso\":186901,\"fecha_de_notificaci_n\":\"2020-06-30 00:00:00\",\"departamento\":25,\"departamento_nom\":\"CUNDINAMARCA\",\"ciudad_municipio\":25473,\"ciudad_municipio_nom\":\"MOSQUERA\",\"edad\":18},\"51\":{\"fecha_reporte_web\":\"2020-12-24 00:00:00\",\"id_de_caso\":1556950,\"fecha_de_notificaci_n\":\"2020-12-18 00:00:00\",\"departamento\":76,\"departamento_nom\":\"VALLE\",\"ciudad_municipio\":76001,\"ciudad_municipio_nom\":\"CALI\",\"edad\":78},\"115\":{\"fecha_reporte_web\":\"2020-08-05 00:00:00\",\"id_de_caso\":338086,\"fecha_de_notificaci_n\":\"2020-07-30 00:00:00\",\"departamento\":76,\"departamento_nom\":\"VALLE\",\"ciudad_municipio\":76001,\"ciudad_municipio_nom\":\"CALI\",\"edad\":25},\"865\":{\"fecha_reporte_web\":\"2021-01-07 00:00:00\",\"id_de_caso\":1734667,\"fecha_de_notificaci_n\":\"2021-01-02 00:00:00\",\"departamento\":76,\"departamento_nom\":\"VALLE\",\"ciudad_municipio\":76001,\"ciudad_municipio_nom\":\"CALI\",\"edad\":36},\"186\":{\"fecha_reporte_web\":\"2021-01-14 00:00:00\",\"id_de_caso\":1841916,\"fecha_de_notificaci_n\":\"2021-01-11 00:00:00\",\"departamento\":11,\"departamento_nom\":\"BOGOTA\",\"ciudad_municipio\":11001,\"ciudad_municipio_nom\":\"BOGOTA\",\"edad\":23}} \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>fecha_reporte_web</th> <th>id_de_caso</th> <th>fecha_de_notificaci_n</th> <th>departamento</th> <th>departamento_nom</th> <th>ciudad_municipio</th> <th>ciudad_municipio_nom</th> <th>edad</th> </tr> </thead> <tbody> <tr> <td>2020-09-03 00:00:00</td> <td>640218</td> <td>2020-08-10 00:00:00</td> <td>5</td> <td>ANTIOQUIA</td> <td>5631</td> <td>SABANETA</td> <td>53</td> </tr> <tr> <td>2020-06-25 00:00:00</td> <td>78509</td> <td>2020-06-19 00:00:00</td> <td>70</td> <td>SUCRE</td> <td>70001</td> <td>SINCELEJO</td> <td>31</td> </tr> <tr> <td>2020-07-18 00:00:00</td> <td>186899</td> <td>2020-06-30 00:00:00</td> <td>13001</td> <td>CARTAGENA</td> <td>13001</td> <td>CARTAGENA</td> <td>62</td> </tr> <tr> <td>2020-09-03 00:00:00</td> <td>640672</td> <td>2020-08-21 00:00:00</td> <td>5</td> <td>ANTIOQUIA</td> <td>5088</td> <td>BELLO</td> <td>67</td> </tr> <tr> <td>2020-07-18 00:00:00</td> <td>186936</td> <td>2020-06-29 00:00:00</td> <td>47001</td> <td>STA MARTA D.E.</td> <td>47001</td> <td>SANTA MARTA</td> <td>48</td> </tr> <tr> <td>2021-01-14 00:00:00</td> <td>1841876</td> <td>2021-01-12 00:00:00</td> <td>11</td> <td>BOGOTA</td> <td>11001</td> <td>BOGOTA</td> <td>34</td> </tr> <tr> <td>2020-07-18 00:00:00</td> <td>186901</td> <td>2020-06-30 00:00:00</td> <td>25</td> <td>CUNDINAMARCA</td> <td>25473</td> <td>MOSQUERA</td> <td>18</td> </tr> <tr> <td>2020-12-24 00:00:00</td> <td>1556950</td> <td>2020-12-18 00:00:00</td> <td>76</td> <td>VALLE</td> <td>76001</td> <td>CALI</td> <td>78</td> </tr> <tr> <td>2020-08-05 00:00:00</td> <td>338086</td> <td>2020-07-30 00:00:00</td> <td>76</td> <td>VALLE</td> <td>76001</td> <td>CALI</td> <td>25</td> </tr> <tr> <td>2021-01-07 00:00:00</td> <td>1734667</td> <td>2021-01-02 00:00:00</td> <td>76</td> <td>VALLE</td> <td>76001</td> <td>CALI</td> <td>36</td> </tr> <tr> <td>2021-01-14 00:00:00</td> <td>1841916</td> <td>2021-01-11 00:00:00</td> <td>11</td> <td>BOGOTA</td> <td>11001</td> <td>BOGOTA</td> <td>23</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
af06a250c4d58799cd7bf0f73df94134106098b21d8b0a3a3e61dd9eacda6724
data_analysis
[ "Please convert the Input Table from CSV format to TSV format. Please respond only with the table. \n Input Table: :@computed_region_43wa_7qmu,location,case_,date_of_occurrence,block,y_coordinate,_primary_decsription,latitude\n5.0,{'latitude': '42.018,JG481551,2023-10-28T00:07:00.,075XX N PAULINA ST,1950023,CRIMINAL DAMAGE,42.018498254\n22.0,{'latitude': '41.705,JG513212,2023-11-21T19:28:00.,010XX W 103RD PL,1836186,ASSAULT,41.70595701\n36.0,{'latitude': '41.876,JG526062,2023-11-30T21:00:00.,002XX W VAN BUREN ST,1898485,CRIMINAL DAMAGE,41.87683815\n8.0,{'latitude': '41.807,JG519147,2023-11-21T12:30:00.,046XX W 47TH ST,1873061,THEFT,41.807662149\n46.0,{'latitude': '41.909,JG561296,2023-12-31T22:34:00.,015XX N SEDGWICK ST,1910545,BATTERY,41.909959349\n24.0,{'latitude': '41.979,JG496701,2023-11-08T16:39:00.,025XX W BALMORAL AVE,1935772,OTHER OFFENSE,41.979505088\n23.0,{'latitude': '41.878,JG512547,2023-11-21T08:45:00.,040XX W WILCOX ST,1899030,NARCOTICS,41.878858482\n31.0,{'latitude': '41.749,JG492993,2023-11-05T22:04:00.,079XX S SANGAMON ST,1852130,BATTERY,41.749707624\n40.0,{'latitude': '41.937,JG542128,2023-12-15T00:00:00.,030XX N ASHLAND AVE,1920425,THEFT,41.937249995\n43.0,{'latitude': '41.707,JH117137,2024-01-16T10:52:00.,102XX S MICHIGAN AVE,1836918,OTHER OFFENSE,41.707793505\n38.0,{'latitude': '41.997,JG496744,2023-11-08T16:41:00.,054XX W DEVON AVE,1942130,BATTERY,41.997327626\n36.0,{'latitude': '41.890,JG560653,2023-12-31T09:30:00.,004XX N ORLEANS ST,1903356,THEFT,41.890221601\n \n Output: \n" ]
:@computed_region_43wa_7qmu location case_ date_of_occurrence block y_coordinate _primary_decsription latitude 5.0 {'latitude': '42.018 JG481551 2023-10-28T00:07:00. 075XX N PAULINA ST 1950023 CRIMINAL DAMAGE 42.018498254 22.0 {'latitude': '41.705 JG513212 2023-11-21T19:28:00. 010XX W 103RD PL 1836186 ASSAULT 41.70595701 36.0 {'latitude': '41.876 JG526062 2023-11-30T21:00:00. 002XX W VAN BUREN ST 1898485 CRIMINAL DAMAGE 41.87683815 8.0 {'latitude': '41.807 JG519147 2023-11-21T12:30:00. 046XX W 47TH ST 1873061 THEFT 41.807662149 46.0 {'latitude': '41.909 JG561296 2023-12-31T22:34:00. 015XX N SEDGWICK ST 1910545 BATTERY 41.909959349 24.0 {'latitude': '41.979 JG496701 2023-11-08T16:39:00. 025XX W BALMORAL AVE 1935772 OTHER OFFENSE 41.979505088 23.0 {'latitude': '41.878 JG512547 2023-11-21T08:45:00. 040XX W WILCOX ST 1899030 NARCOTICS 41.878858482 31.0 {'latitude': '41.749 JG492993 2023-11-05T22:04:00. 079XX S SANGAMON ST 1852130 BATTERY 41.749707624 40.0 {'latitude': '41.937 JG542128 2023-12-15T00:00:00. 030XX N ASHLAND AVE 1920425 THEFT 41.937249995 43.0 {'latitude': '41.707 JH117137 2024-01-16T10:52:00. 102XX S MICHIGAN AVE 1836918 OTHER OFFENSE 41.707793505 38.0 {'latitude': '41.997 JG496744 2023-11-08T16:41:00. 054XX W DEVON AVE 1942130 BATTERY 41.997327626 36.0 {'latitude': '41.890 JG560653 2023-12-31T09:30:00. 004XX N ORLEANS ST 1903356 THEFT 41.890221601
tablereformat
2024-06-24T00:00:00
fe2193c57ea45001a4926fe79284b5a1405531d70f8ff5e5a4ebfeea8a79a10e
data_analysis
[ "Please convert the Input Table from HTML format to TSV format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>처방번호</th>\n <th>처방명(한글)</th>\n <th>처방명(한문)</th>\n <th>원전(한글)</th>\n <th>원전(한문)</th>\n <th>약재명(한글)</th>\n <th>약재명(한문)</th>\n <th>함량(g)</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>47</td>\n <td>청서익기탕</td>\n <td>淸署益氣湯</td>\n <td>방약합편</td>\n <td>方藥合編</td>\n <td>황기</td>\n <td>黃芪</td>\n <td>3.75</td>\n </tr>\n <tr>\n <td>7</td>\n <td>내소산</td>\n <td>內消散</td>\n <td>방약합편</td>\n <td>方藥合編</td>\n <td>아출</td>\n <td>莪朮</td>\n <td>3.75</td>\n </tr>\n <tr>\n <td>37</td>\n <td>오림산</td>\n <td>五淋散</td>\n <td>방약합편</td>\n <td>方藥合編</td>\n <td>치자</td>\n <td>梔子</td>\n <td>7.50</td>\n </tr>\n <tr>\n <td>19</td>\n <td>보중익기탕</td>\n <td>補中益氣湯</td>\n <td>방약합편</td>\n <td>方藥合編</td>\n <td>황기</td>\n <td>黃芪</td>\n <td>5.63</td>\n </tr>\n <tr>\n <td>21</td>\n <td>복령보심탕</td>\n <td>茯苓補心湯</td>\n <td>방약합편</td>\n <td>方藥合編</td>\n <td>진피</td>\n <td>陳皮</td>\n <td>1.88</td>\n </tr>\n <tr>\n <td>50</td>\n <td>평위산</td>\n <td>平胃散</td>\n <td>동의보감</td>\n <td>東醫寶鑑</td>\n <td>대추</td>\n <td>大棗</td>\n <td>2.00</td>\n </tr>\n <tr>\n <td>52</td>\n <td>향사평위산</td>\n <td>香砂平胃散</td>\n <td>방약합편</td>\n <td>方藥合編</td>\n <td>목향</td>\n <td>木香</td>\n <td>1.88</td>\n </tr>\n <tr>\n <td>50</td>\n <td>평위산</td>\n <td>平胃散</td>\n <td>동의보감</td>\n <td>東醫寶鑑</td>\n <td>생강</td>\n <td>生薑</td>\n <td>1.50</td>\n </tr>\n <tr>\n <td>49</td>\n <td>팔물탕</td>\n <td>八物湯</td>\n <td>방약합편</td>\n <td>方藥合編</td>\n <td>천궁</td>\n <td>川芎</td>\n <td>4.50</td>\n </tr>\n <tr>\n <td>35</td>\n <td>안태음</td>\n <td>安胎飮</td>\n <td>동의보감</td>\n <td>東醫寶鑑</td>\n <td>황금</td>\n <td>黃芩</td>\n <td>5.63</td>\n </tr>\n <tr>\n <td>19</td>\n <td>보중익기탕</td>\n <td>補中益氣湯</td>\n <td>방약합편</td>\n <td>方藥合編</td>\n <td>인삼</td>\n <td>人蔘</td>\n <td>3.75</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
처방번호 처방명(한글) 처방명(한문) 원전(한글) 원전(한문) 약재명(한글) 약재명(한문) 함량(g) 47 청서익기탕 淸署益氣湯 방약합편 方藥合編 황기 黃芪 3.75 7 내소산 內消散 방약합편 方藥合編 아출 莪朮 3.75 37 오림산 五淋散 방약합편 方藥合編 치자 梔子 7.5 19 보중익기탕 補中益氣湯 방약합편 方藥合編 황기 黃芪 5.63 21 복령보심탕 茯苓補心湯 방약합편 方藥合編 진피 陳皮 1.88 50 평위산 平胃散 동의보감 東醫寶鑑 대추 大棗 2.0 52 향사평위산 香砂平胃散 방약합편 方藥合編 목향 木香 1.88 50 평위산 平胃散 동의보감 東醫寶鑑 생강 生薑 1.5 49 팔물탕 八物湯 방약합편 方藥合編 천궁 川芎 4.5 35 안태음 安胎飮 동의보감 東醫寶鑑 황금 黃芩 5.63 19 보중익기탕 補中益氣湯 방약합편 方藥合編 인삼 人蔘 3.75
tablereformat
2024-06-24T00:00:00
f2dcd6a353c4390c3d98c8d4ff03d778f00d0d6c6b9f8238af4f09f81f6d9924
data_analysis
[ "Please convert the Input Table from JSON format to CSV format. Please respond only with the table. \n Input Table: {\"151\":{\"Country\":\"Comoros\",\"Inequality HDI\":3},\"13\":{\"Country\":\"Liechtenstein\",\"Inequality HDI\":0},\"91\":{\"Country\":\"Libya\",\"Inequality HDI\":2},\"165\":{\"Country\":\"C\\u00f4te d'Ivoire\",\"Inequality HDI\":3},\"30\":{\"Country\":\"Estonia\",\"Inequality HDI\":0},\"53\":{\"Country\":\"Antigua and Barbuda\",\"Inequality HDI\":0},\"63\":{\"Country\":\"Costa Rica\",\"Inequality HDI\":2},\"95\":{\"Country\":\"Mongolia\",\"Inequality HDI\":2},\"33\":{\"Country\":\"Bahrain\",\"Inequality HDI\":0},\"173\":{\"Country\":\"Gambia\",\"Inequality HDI\":3}} \n Output: \n" ]
Country,Inequality HDI Comoros,3 Liechtenstein,0 Libya,2 Côte d'Ivoire,3 Estonia,0 Antigua and Barbuda,0 Costa Rica,2 Mongolia,2 Bahrain,0 Gambia,3
tablereformat
2024-06-24T00:00:00
4d22f4f91dfc8188c2244048d968e9885ee063658c14fcf43c8156983f5a395f
data_analysis
[ "Please convert the Input Table from TSV format to HTML format. Please respond only with the table. \n Input Table: name\tid\tnametype\trecclass\tmass\tfall\tyear\treclat\nOvambo\t18055\tValid\tL6\t121.5\tFell\t1900-01-01T00:00:00.\t-18.0\nAndura\t2298\tValid\tH6\t17900.0\tFell\t1939-01-01T00:00:00.\t20.88333\nPetersburg\t18801\tValid\tEucrite-pmict\t1800.0\tFell\t1855-01-01T00:00:00.\t35.3\nMeester-Cornelis\t15470\tValid\tH5\t24750.0\tFell\t1915-01-01T00:00:00.\t-6.23333\nBhagur\t5037\tValid\tL6\t18.0\tFell\t1877-01-01T00:00:00.\t20.88333\nHachi-oji\t11468\tValid\tH?\t0.2\tFell\t1817-01-01T00:00:00.\t35.65\nTagish Lake\t23782\tValid\tC2-ung\t10000.0\tFell\t2000-01-01T00:00:00.\t59.70444\nChicora\t5349\tValid\tLL6\t303.0\tFell\t1938-01-01T00:00:00.\t40.93333\nOterøy\t18042\tValid\tL6\t246.0\tFell\t1928-01-01T00:00:00.\t58.88333\nMoore County\t16736\tValid\tEucrite-cm\t1880.0\tFell\t1913-01-01T00:00:00.\t35.41667\nConquista\t5418\tValid\tH4\t20350.0\tFell\t1965-01-01T00:00:00.\t-19.85\nKagarlyk\t12227\tValid\tL6\t1900.0\tFell\t1908-01-01T00:00:00.\t49.86667\nItapicuru-Mirim\t12056\tValid\tH5\t2024.0\tFell\t1879-01-01T00:00:00.\t-3.4\n \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>name</th> <th>id</th> <th>nametype</th> <th>recclass</th> <th>mass</th> <th>fall</th> <th>year</th> <th>reclat</th> </tr> </thead> <tbody> <tr> <td>Ovambo</td> <td>18055</td> <td>Valid</td> <td>L6</td> <td>121.5</td> <td>Fell</td> <td>1900-01-01T00:00:00.</td> <td>-18.00000</td> </tr> <tr> <td>Andura</td> <td>2298</td> <td>Valid</td> <td>H6</td> <td>17900.0</td> <td>Fell</td> <td>1939-01-01T00:00:00.</td> <td>20.88333</td> </tr> <tr> <td>Petersburg</td> <td>18801</td> <td>Valid</td> <td>Eucrite-pmict</td> <td>1800.0</td> <td>Fell</td> <td>1855-01-01T00:00:00.</td> <td>35.30000</td> </tr> <tr> <td>Meester-Cornelis</td> <td>15470</td> <td>Valid</td> <td>H5</td> <td>24750.0</td> <td>Fell</td> <td>1915-01-01T00:00:00.</td> <td>-6.23333</td> </tr> <tr> <td>Bhagur</td> <td>5037</td> <td>Valid</td> <td>L6</td> <td>18.0</td> <td>Fell</td> <td>1877-01-01T00:00:00.</td> <td>20.88333</td> </tr> <tr> <td>Hachi-oji</td> <td>11468</td> <td>Valid</td> <td>H?</td> <td>0.2</td> <td>Fell</td> <td>1817-01-01T00:00:00.</td> <td>35.65000</td> </tr> <tr> <td>Tagish Lake</td> <td>23782</td> <td>Valid</td> <td>C2-ung</td> <td>10000.0</td> <td>Fell</td> <td>2000-01-01T00:00:00.</td> <td>59.70444</td> </tr> <tr> <td>Chicora</td> <td>5349</td> <td>Valid</td> <td>LL6</td> <td>303.0</td> <td>Fell</td> <td>1938-01-01T00:00:00.</td> <td>40.93333</td> </tr> <tr> <td>Oterøy</td> <td>18042</td> <td>Valid</td> <td>L6</td> <td>246.0</td> <td>Fell</td> <td>1928-01-01T00:00:00.</td> <td>58.88333</td> </tr> <tr> <td>Moore County</td> <td>16736</td> <td>Valid</td> <td>Eucrite-cm</td> <td>1880.0</td> <td>Fell</td> <td>1913-01-01T00:00:00.</td> <td>35.41667</td> </tr> <tr> <td>Conquista</td> <td>5418</td> <td>Valid</td> <td>H4</td> <td>20350.0</td> <td>Fell</td> <td>1965-01-01T00:00:00.</td> <td>-19.85000</td> </tr> <tr> <td>Kagarlyk</td> <td>12227</td> <td>Valid</td> <td>L6</td> <td>1900.0</td> <td>Fell</td> <td>1908-01-01T00:00:00.</td> <td>49.86667</td> </tr> <tr> <td>Itapicuru-Mirim</td> <td>12056</td> <td>Valid</td> <td>H5</td> <td>2024.0</td> <td>Fell</td> <td>1879-01-01T00:00:00.</td> <td>-3.40000</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
e321ff8846ddd951d029b63efd6f0cdadb5b6daae266e3b21a6f3e805faf75e4
data_analysis
[ "Please convert the Input Table from JSONL format to TSV format. Please respond only with the table. \n Input Table: {\"Review Text\":\"This book opened my \",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"I learned about fina\",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"Love the story, and \",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"It looks good, the f\",\"Rating\":\"4.0 out of 5 stars\"}\n{\"Review Text\":\"Perspective.\",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"It is an absolute ga\",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"Such a great read\",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"Awesome Book- Easy r\",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"Wish I had read this\",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"This book will chang\",\"Rating\":\"5.0 out of 5 stars\"}\n{\"Review Text\":\"Ordered the paperbac\",\"Rating\":\"4.0 out of 5 stars\"}\n \n Output: \n" ]
Review Text Rating This book opened my 5.0 out of 5 stars I learned about fina 5.0 out of 5 stars Love the story, and 5.0 out of 5 stars It looks good, the f 4.0 out of 5 stars Perspective. 5.0 out of 5 stars It is an absolute ga 5.0 out of 5 stars Such a great read 5.0 out of 5 stars Awesome Book- Easy r 5.0 out of 5 stars Wish I had read this 5.0 out of 5 stars This book will chang 5.0 out of 5 stars Ordered the paperbac 4.0 out of 5 stars
tablereformat
2024-06-24T00:00:00
dbc100e6b17f59547b155762e53564c1d30e21197f86780b166e4c067ee4b0e8
data_analysis
[ "Please convert the Input Table from JSON format to CSV format. Please respond only with the table. \n Input Table: {\"743\":{\"res_geo_short\":\"Yuba\",\"work_geo_short\":\"Nevada\",\"year\":2016,\"total\":970,\"drove_alone\":750,\"_2_person_carpool\":170,\"_3_person_carpool\":45,\"_4_person_carpool\":0},\"428\":{\"res_geo_short\":\"San Joaquin\",\"work_geo_short\":\"Lake\",\"year\":2016,\"total\":20,\"drove_alone\":0,\"_2_person_carpool\":20,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"941\":{\"res_geo_short\":\"San Mateo\",\"work_geo_short\":\"San Benito\",\"year\":2016,\"total\":25,\"drove_alone\":25,\"_2_person_carpool\":0,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"986\":{\"res_geo_short\":\"Madera\",\"work_geo_short\":\"San Diego\",\"year\":2016,\"total\":40,\"drove_alone\":10,\"_2_person_carpool\":0,\"_3_person_carpool\":10,\"_4_person_carpool\":0},\"943\":{\"res_geo_short\":\"Santa Cruz\",\"work_geo_short\":\"San Benito\",\"year\":2016,\"total\":545,\"drove_alone\":385,\"_2_person_carpool\":80,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"980\":{\"res_geo_short\":\"Contra Costa\",\"work_geo_short\":\"San Diego\",\"year\":2016,\"total\":230,\"drove_alone\":190,\"_2_person_carpool\":15,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"798\":{\"res_geo_short\":\"Napa\",\"work_geo_short\":\"Placer\",\"year\":2016,\"total\":15,\"drove_alone\":15,\"_2_person_carpool\":0,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"79\":{\"res_geo_short\":\"Butte\",\"work_geo_short\":\"Butte\",\"year\":2016,\"total\":80320,\"drove_alone\":59770,\"_2_person_carpool\":6305,\"_3_person_carpool\":1445,\"_4_person_carpool\":340},\"151\":{\"res_geo_short\":\"Yolo\",\"work_geo_short\":\"Colusa\",\"year\":2016,\"total\":280,\"drove_alone\":280,\"_2_person_carpool\":0,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"518\":{\"res_geo_short\":\"Tulare\",\"work_geo_short\":\"Madera\",\"year\":2016,\"total\":255,\"drove_alone\":175,\"_2_person_carpool\":60,\"_3_person_carpool\":0,\"_4_person_carpool\":20},\"594\":{\"res_geo_short\":\"Sonoma\",\"work_geo_short\":\"Mendocino\",\"year\":2016,\"total\":1030,\"drove_alone\":965,\"_2_person_carpool\":55,\"_3_person_carpool\":0,\"_4_person_carpool\":0},\"271\":{\"res_geo_short\":\"Stanislaus\",\"work_geo_short\":\"Fresno\",\"year\":2016,\"total\":555,\"drove_alone\":390,\"_2_person_carpool\":30,\"_3_person_carpool\":45,\"_4_person_carpool\":0}} \n Output: \n" ]
res_geo_short,work_geo_short,year,total,drove_alone,_2_person_carpool,_3_person_carpool,_4_person_carpool Yuba,Nevada,2016,970,750,170,45,0 San Joaquin,Lake,2016,20,0,20,0,0 San Mateo,San Benito,2016,25,25,0,0,0 Madera,San Diego,2016,40,10,0,10,0 Santa Cruz,San Benito,2016,545,385,80,0,0 Contra Costa,San Diego,2016,230,190,15,0,0 Napa,Placer,2016,15,15,0,0,0 Butte,Butte,2016,80320,59770,6305,1445,340 Yolo,Colusa,2016,280,280,0,0,0 Tulare,Madera,2016,255,175,60,0,20 Sonoma,Mendocino,2016,1030,965,55,0,0 Stanislaus,Fresno,2016,555,390,30,45,0
tablereformat
2024-06-24T00:00:00
083282355242eb434e4c4559eabea700f94928fd2e1d0d4df6a59ee143866e60
data_analysis
[ "Please convert the Input Table from CSV format to JSONL format. Please respond only with the table. \n Input Table: species,quantity\nSPLAKE,144790\nBROOK TROUT,232058\nSUNFISH BLUEGILL,47840\nSUCKER JUNE,80510\nBASS LARGEMOUTH,22765\nBULLHEAD CHANNEL CAT,183295\nKOKANEE,716220\nLAKE TROUT,2931\nGOLDEN TROUT,4581\nTIGER TROUT,401119\nGRAYLING ARCTIC,84211\nCHUB,34740\nALL TROUT,1650\nRAINBOW,3904196\n \n Output: \n" ]
{"species":"SPLAKE","quantity":144790} {"species":"BROOK TROUT","quantity":232058} {"species":"SUNFISH BLUEGILL","quantity":47840} {"species":"SUCKER JUNE","quantity":80510} {"species":"BASS LARGEMOUTH","quantity":22765} {"species":"BULLHEAD CHANNEL CAT","quantity":183295} {"species":"KOKANEE","quantity":716220} {"species":"LAKE TROUT","quantity":2931} {"species":"GOLDEN TROUT","quantity":4581} {"species":"TIGER TROUT","quantity":401119} {"species":"GRAYLING ARCTIC","quantity":84211} {"species":"CHUB","quantity":34740} {"species":"ALL TROUT","quantity":1650} {"species":"RAINBOW","quantity":3904196}
tablereformat
2024-06-24T00:00:00
804182061bd3648a5d1079e9836aa8cb7e9201a32f190863551299075fbeac47
data_analysis
[ "Please convert the Input Table from HTML format to TSV format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>interaction_id</th>\n <th>query_time</th>\n <th>domain</th>\n <th>question_type</th>\n <th>static_or_dynamic</th>\n <th>query</th>\n <th>answer</th>\n <th>alternative_answers</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>ee0b351c-5a00-48e2-9</td>\n <td>03/19/2024, 23:49:23</td>\n <td>movie</td>\n <td>simple</td>\n <td>static</td>\n <td>in 2008, which movie</td>\n <td>the golden compass</td>\n <td>[]</td>\n </tr>\n <tr>\n <td>d660a07b-c598-4be9-b</td>\n <td>03/19/2024, 23:34:54</td>\n <td>movie</td>\n <td>simple</td>\n <td>static</td>\n <td>which movie was reco</td>\n <td>ratatouille</td>\n <td>[]</td>\n </tr>\n <tr>\n <td>42163b55-9bf6-4412-a</td>\n <td>03/15/2024, 17:05:41</td>\n <td>sports</td>\n <td>comparison</td>\n <td>static</td>\n <td>during the 2022-12 s</td>\n <td>true</td>\n <td>[]</td>\n </tr>\n <tr>\n <td>82e66a91-22eb-4806-a</td>\n <td>03/05/2024, 23:19:09</td>\n <td>music</td>\n <td>simple_w_condition</td>\n <td>static</td>\n <td>what is the song tha</td>\n <td>cold heart</td>\n <td>[]</td>\n </tr>\n <tr>\n <td>a91df871-089c-4b91-9</td>\n <td>03/19/2024, 23:17:23</td>\n <td>movie</td>\n <td>simple</td>\n <td>static</td>\n <td>who directed bridget</td>\n <td>beeban kidron</td>\n <td>[]</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
interaction_id query_time domain question_type static_or_dynamic query answer alternative_answers ee0b351c-5a00-48e2-9 03/19/2024, 23:49:23 movie simple static in 2008, which movie the golden compass [] d660a07b-c598-4be9-b 03/19/2024, 23:34:54 movie simple static which movie was reco ratatouille [] 42163b55-9bf6-4412-a 03/15/2024, 17:05:41 sports comparison static during the 2022-12 s true [] 82e66a91-22eb-4806-a 03/05/2024, 23:19:09 music simple_w_condition static what is the song tha cold heart [] a91df871-089c-4b91-9 03/19/2024, 23:17:23 movie simple static who directed bridget beeban kidron []
tablereformat
2024-06-24T00:00:00
16b99f3754472adfba51046b35d0bb8af8d7e95e8dbac50d5f0f82b9775229df
data_analysis
[ "Please convert the Input Table from JSON format to CSV format. Please respond only with the table. \n Input Table: {\"39\":{\"basisid\":\"27920239-c9fd-4a31-a\",\"data_category\":\"Environment\",\"data_subcategory\":\"Climate\",\"data_set\":\"Adapting to Rising T\",\"description\":\"This feature set is \",\"data_steward\":\"Michael Smith\",\"primary_uses\":\"Resiliance Programs;\",\"format\":\"geo\"},\"9\":{\"basisid\":\"21c09c97-9ed5-436b-b\",\"data_category\":\"Environment\",\"data_subcategory\":\"Natural Hazards\",\"data_set\":\"CalFire Fire Severit\",\"description\":\"Features represent F\",\"data_steward\":\"Michael Germeraad\",\"primary_uses\":\"Resiliance Programs;\",\"format\":\"geo\"},\"21\":{\"basisid\":\"db70c05e-7741-11e9-8\",\"data_category\":\"Environment\",\"data_subcategory\":\"Natural Hazards\",\"data_set\":\"Shaking Scenarios\",\"description\":\"Projected intensitie\",\"data_steward\":\"Michael Germeraad\",\"primary_uses\":\"Resiliance Programs;\",\"format\":\"geo\"},\"15\":{\"basisid\":\"db70b30c-7741-11e9-8\",\"data_category\":\"Environment\",\"data_subcategory\":\"Natural Hazards\",\"data_set\":\"Liquefaction Study Z\",\"description\":\"Liquefaction hazard \",\"data_steward\":\"Michael Germeraad\",\"primary_uses\":\"Resiliance Programs;\",\"format\":\"geo\"},\"24\":{\"basisid\":\"db70cb44-7741-11e9-8\",\"data_category\":\"Environment\",\"data_subcategory\":\"Natural Hazards\",\"data_set\":\"Wildfire Threat\",\"description\":\"Wildland fire threat\",\"data_steward\":\"Michael Germeraad\",\"primary_uses\":\"Resiliance Programs;\",\"format\":\"geo\"},\"27\":{\"basisid\":\"db70a0e2-7741-11e9-8\",\"data_category\":\"Land & People\",\"data_subcategory\":\"Buildings\",\"data_set\":\"Buildings\",\"description\":\"The parcel\\/building \",\"data_steward\":\"Michael Reilly\",\"primary_uses\":\"UrbanSim Modeling\",\"format\":\"table\"},\"10\":{\"basisid\":\"db70c306-7741-11e9-8\",\"data_category\":\"Environment\",\"data_subcategory\":\"Natural Hazards\",\"data_set\":\"Debris Flow Source A\",\"description\":\"Debris flow source a\",\"data_steward\":\"Michael Germeraad\",\"primary_uses\":\"Resiliance Programs;\",\"format\":\"geo\"},\"43\":{\"basisid\":\"6ccfe813-61a5-46cf-b\",\"data_category\":\"Environment\",\"data_subcategory\":\"Species Habitat\",\"data_set\":\"Critical Habitat for\",\"description\":\"When a species is pr\",\"data_steward\":\"Michael Smith\",\"primary_uses\":\"UrbanSim Modeling; P\",\"format\":\"geo\"},\"25\":{\"basisid\":\"db70cc8e-7741-11e9-8\",\"data_category\":\"Environment\",\"data_subcategory\":\"Natural Hazards\",\"data_set\":\"Wildland-Urban Inter\",\"description\":\"Threat areas for the\",\"data_steward\":\"Michael Germeraad\",\"primary_uses\":\"Resiliance Programs;\",\"format\":\"geo\"}} \n Output: \n" ]
basisid,data_category,data_subcategory,data_set,description,data_steward,primary_uses,format 27920239-c9fd-4a31-a,Environment,Climate,Adapting to Rising T,This feature set is ,Michael Smith,Resiliance Programs;,geo 21c09c97-9ed5-436b-b,Environment,Natural Hazards,CalFire Fire Severit,Features represent F,Michael Germeraad,Resiliance Programs;,geo db70c05e-7741-11e9-8,Environment,Natural Hazards,Shaking Scenarios,Projected intensitie,Michael Germeraad,Resiliance Programs;,geo db70b30c-7741-11e9-8,Environment,Natural Hazards,Liquefaction Study Z,Liquefaction hazard ,Michael Germeraad,Resiliance Programs;,geo db70cb44-7741-11e9-8,Environment,Natural Hazards,Wildfire Threat,Wildland fire threat,Michael Germeraad,Resiliance Programs;,geo db70a0e2-7741-11e9-8,Land & People,Buildings,Buildings,The parcel/building ,Michael Reilly,UrbanSim Modeling,table db70c306-7741-11e9-8,Environment,Natural Hazards,Debris Flow Source A,Debris flow source a,Michael Germeraad,Resiliance Programs;,geo 6ccfe813-61a5-46cf-b,Environment,Species Habitat,Critical Habitat for,When a species is pr,Michael Smith,UrbanSim Modeling; P,geo db70cc8e-7741-11e9-8,Environment,Natural Hazards,Wildland-Urban Inter,Threat areas for the,Michael Germeraad,Resiliance Programs;,geo
tablereformat
2024-06-24T00:00:00
00d7be878c842d12814cb113caf8503525f8cf845b7d3ca4b8387c843f06ebc9
data_analysis
[ "Please convert the Input Table from CSV format to HTML format. Please respond only with the table. \n Input Table: Unnamed: 0,fecha,hora,sistema,bandera,precio,tipo_moneda,origen_dato\n915475,2017-11-27,15,RS,0,75.55,1,5\n44001,2013-02-22,4,EE,0,39.05,1,2\n1778281,2021-11-04,18,CSUD,0,250.0,1,8\n10955,2011-10-20,12,HU,1,72.322,1,6\n1760435,2021-10-13,22,EE,1,170.54,1,2\n797217,2017-04-17,17,LT,1,28.05,1,2\n1258422,2019-08-28,24,SE3,1,35.64,1,2\n108523,2013-07-21,13,NO5,1,35.11,1,2\n252656,2014-05-26,21,SE1,1,42.29,1,2\n637038,2016-06-18,8,NO2,1,23.36,1,2\n606399,2016-04-21,7,SE2,1,21.89,1,2\n1132360,2019-01-12,10,ES,0,68.0,1,1\n570188,2016-02-13,6,NO4,0,18.13,1,2\n \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>Unnamed: 0</th> <th>fecha</th> <th>hora</th> <th>sistema</th> <th>bandera</th> <th>precio</th> <th>tipo_moneda</th> <th>origen_dato</th> </tr> </thead> <tbody> <tr> <td>915475</td> <td>2017-11-27</td> <td>15</td> <td>RS</td> <td>0</td> <td>75.550</td> <td>1</td> <td>5</td> </tr> <tr> <td>44001</td> <td>2013-02-22</td> <td>4</td> <td>EE</td> <td>0</td> <td>39.050</td> <td>1</td> <td>2</td> </tr> <tr> <td>1778281</td> <td>2021-11-04</td> <td>18</td> <td>CSUD</td> <td>0</td> <td>250.000</td> <td>1</td> <td>8</td> </tr> <tr> <td>10955</td> <td>2011-10-20</td> <td>12</td> <td>HU</td> <td>1</td> <td>72.322</td> <td>1</td> <td>6</td> </tr> <tr> <td>1760435</td> <td>2021-10-13</td> <td>22</td> <td>EE</td> <td>1</td> <td>170.540</td> <td>1</td> <td>2</td> </tr> <tr> <td>797217</td> <td>2017-04-17</td> <td>17</td> <td>LT</td> <td>1</td> <td>28.050</td> <td>1</td> <td>2</td> </tr> <tr> <td>1258422</td> <td>2019-08-28</td> <td>24</td> <td>SE3</td> <td>1</td> <td>35.640</td> <td>1</td> <td>2</td> </tr> <tr> <td>108523</td> <td>2013-07-21</td> <td>13</td> <td>NO5</td> <td>1</td> <td>35.110</td> <td>1</td> <td>2</td> </tr> <tr> <td>252656</td> <td>2014-05-26</td> <td>21</td> <td>SE1</td> <td>1</td> <td>42.290</td> <td>1</td> <td>2</td> </tr> <tr> <td>637038</td> <td>2016-06-18</td> <td>8</td> <td>NO2</td> <td>1</td> <td>23.360</td> <td>1</td> <td>2</td> </tr> <tr> <td>606399</td> <td>2016-04-21</td> <td>7</td> <td>SE2</td> <td>1</td> <td>21.890</td> <td>1</td> <td>2</td> </tr> <tr> <td>1132360</td> <td>2019-01-12</td> <td>10</td> <td>ES</td> <td>0</td> <td>68.000</td> <td>1</td> <td>1</td> </tr> <tr> <td>570188</td> <td>2016-02-13</td> <td>6</td> <td>NO4</td> <td>0</td> <td>18.130</td> <td>1</td> <td>2</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
0e5a359e5a70462b866ffd40a10f0b976ed63030be062c8a9eb8c72316ac2146
data_analysis
[ "Please convert the Input Table from CSV format to HTML format. Please respond only with the table. \n Input Table: plan_strategy,rtpid,title,scope,open_period,funding_millions_yoe,county\nRegional Rail,21-T11-111,Rail | Service Expan,This program include,2021 - 2035,305,Alameda\nLocal Transit,21-T10-093,Other Investments to,This program include,Various,3003,Regional\nLocal Transit,21-T10-077,BRT | Modernization ,This program include,2021 - 2035,300,Various\nRegional Rail,21-T11-098,Ferry | Service Expa,This program include,2021 - 2035,472,Various\nInterchanges and Bot,21-T06-021,Corridor & Interchan,This program include,2036 - 2050,94,Alameda\nFix It First,21-T01-007,Other Investments to,This program include,Various,8051,Regional\n \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>plan_strategy</th> <th>rtpid</th> <th>title</th> <th>scope</th> <th>open_period</th> <th>funding_millions_yoe</th> <th>county</th> </tr> </thead> <tbody> <tr> <td>Regional Rail</td> <td>21-T11-111</td> <td>Rail | Service Expan</td> <td>This program include</td> <td>2021 - 2035</td> <td>305</td> <td>Alameda</td> </tr> <tr> <td>Local Transit</td> <td>21-T10-093</td> <td>Other Investments to</td> <td>This program include</td> <td>Various</td> <td>3003</td> <td>Regional</td> </tr> <tr> <td>Local Transit</td> <td>21-T10-077</td> <td>BRT | Modernization</td> <td>This program include</td> <td>2021 - 2035</td> <td>300</td> <td>Various</td> </tr> <tr> <td>Regional Rail</td> <td>21-T11-098</td> <td>Ferry | Service Expa</td> <td>This program include</td> <td>2021 - 2035</td> <td>472</td> <td>Various</td> </tr> <tr> <td>Interchanges and Bot</td> <td>21-T06-021</td> <td>Corridor &amp; Interchan</td> <td>This program include</td> <td>2036 - 2050</td> <td>94</td> <td>Alameda</td> </tr> <tr> <td>Fix It First</td> <td>21-T01-007</td> <td>Other Investments to</td> <td>This program include</td> <td>Various</td> <td>8051</td> <td>Regional</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
0d102a277bdaf52b40a8dc150408f122828ee63f2a55dd0e58f3c7b51933d345
data_analysis
[ "Please convert the Input Table from CSV format to JSONL format. Please respond only with the table. \n Input Table: sample_material,id,mfr,tml,category,cvcm,space_code,wvr\nAD300C WOVEN FIBERGL,GSC32923,ARL,0.03,10,0.01,1,0.01\nABLESTIK 761-6 A/B/V,GSFC7598,AAC,0.36,1,0.0,1,0.23\nAPTEK THERM-PAD 1100,GSC26749,APT,0.11,6,0.02,1,0.0\nBLACK NYLON 6/6 CABL,GSC33049,RCO,2.31,9,0.02,1,0.68\nBEN-HAR EX-FLEX 1500,SRI13401,BHM,0.18,0,0.14,1,\nARMSTRONG C-4/ACT W ,GSC12802,APC,1.33,1,0.04,1,0.38\nABLETHERM 8-2 A/B AS,GSC26023,AAC,0.71,1,0.01,1,0.1\nAMS 3195B RED SILICO,GSC21899,FUJ,0.08,15,0.01,1,0.04\n \n Output: \n" ]
{"sample_material":"AD300C WOVEN FIBERGL","id":"GSC32923","mfr":"ARL","tml":0.03,"category":10,"cvcm":0.01,"space_code":1,"wvr":0.01} {"sample_material":"ABLESTIK 761-6 A\/B\/V","id":"GSFC7598","mfr":"AAC","tml":0.36,"category":1,"cvcm":0.0,"space_code":1,"wvr":0.23} {"sample_material":"APTEK THERM-PAD 1100","id":"GSC26749","mfr":"APT","tml":0.11,"category":6,"cvcm":0.02,"space_code":1,"wvr":0.0} {"sample_material":"BLACK NYLON 6\/6 CABL","id":"GSC33049","mfr":"RCO","tml":2.31,"category":9,"cvcm":0.02,"space_code":1,"wvr":0.68} {"sample_material":"BEN-HAR EX-FLEX 1500","id":"SRI13401","mfr":"BHM","tml":0.18,"category":0,"cvcm":0.14,"space_code":1,"wvr":null} {"sample_material":"ARMSTRONG C-4\/ACT W ","id":"GSC12802","mfr":"APC","tml":1.33,"category":1,"cvcm":0.04,"space_code":1,"wvr":0.38} {"sample_material":"ABLETHERM 8-2 A\/B AS","id":"GSC26023","mfr":"AAC","tml":0.71,"category":1,"cvcm":0.01,"space_code":1,"wvr":0.1} {"sample_material":"AMS 3195B RED SILICO","id":"GSC21899","mfr":"FUJ","tml":0.08,"category":15,"cvcm":0.01,"space_code":1,"wvr":0.04}
tablereformat
2024-06-24T00:00:00
0a9d3c9d94cdbd52adf5852ebdf291b4ff8788032d950f62695d1dcc298b54f6
data_analysis
[ "Please convert the Input Table from JSON format to CSV format. Please respond only with the table. \n Input Table: {\"14\":{\"species\":\"GOLDEN TROUT\",\"quantity\":4581},\"13\":{\"species\":\"BASS LARGEMOUTH\",\"quantity\":22765},\"10\":{\"species\":\"SUCKER JUNE\",\"quantity\":80510},\"0\":{\"species\":\"RAINBOW\",\"quantity\":3904196},\"11\":{\"species\":\"SUNFISH BLUEGILL\",\"quantity\":47840},\"15\":{\"species\":\"WOUNDFIN MINNOW\",\"quantity\":3588},\"17\":{\"species\":\"ALL TROUT\",\"quantity\":1650},\"6\":{\"species\":\"BROOK TROUT\",\"quantity\":232058},\"7\":{\"species\":\"BULLHEAD CHANNEL CAT\",\"quantity\":183295},\"18\":{\"species\":\"MUSKIE TIGER\",\"quantity\":590},\"12\":{\"species\":\"CHUB\",\"quantity\":34740},\"5\":{\"species\":\"BROWN TROUT\",\"quantity\":245553},\"4\":{\"species\":\"WIPER\",\"quantity\":386460},\"2\":{\"species\":\"KOKANEE\",\"quantity\":716220}} \n Output: \n" ]
species,quantity GOLDEN TROUT,4581 BASS LARGEMOUTH,22765 SUCKER JUNE,80510 RAINBOW,3904196 SUNFISH BLUEGILL,47840 WOUNDFIN MINNOW,3588 ALL TROUT,1650 BROOK TROUT,232058 BULLHEAD CHANNEL CAT,183295 MUSKIE TIGER,590 CHUB,34740 BROWN TROUT,245553 WIPER,386460 KOKANEE,716220
tablereformat
2024-06-24T00:00:00
07844eb9fb31c8e9cac12e29662d01c221f762a67418b020ff4eae637065539a
data_analysis
[ "Please convert the Input Table from HTML format to JSONL format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>cleanup_site_name</th>\n <th>location</th>\n <th>zipcode</th>\n <th>city</th>\n <th>responsible_section</th>\n <th>:@computed_region_fny7_vc3j</th>\n <th>:@computed_region_x4ys_rtnd</th>\n <th>region</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>ALBRICI PROPERTY</td>\n <td>{'latitude': '45.673</td>\n <td>98665</td>\n <td>VANCOUVER</td>\n <td>Southwest</td>\n <td>3</td>\n <td>2977.0</td>\n <td>Southwest</td>\n </tr>\n <tr>\n <td>Willard Aldridge &amp; A</td>\n <td>{'latitude': '47.418</td>\n <td>98801</td>\n <td>WENATCHEE</td>\n <td>Central</td>\n <td>8</td>\n <td>2956.0</td>\n <td>Central</td>\n </tr>\n <tr>\n <td>Riverside Residentia</td>\n <td>{'latitude': '45.613</td>\n <td>98661</td>\n <td>VANCOUVER</td>\n <td>Southwest</td>\n <td>3</td>\n <td>2977.0</td>\n <td>Southwest</td>\n </tr>\n <tr>\n <td>ABANDON TANK SITE</td>\n <td>{'latitude': '45.636</td>\n <td>98660-2635</td>\n <td>VANCOUVER</td>\n <td>Southwest</td>\n <td>3</td>\n <td>2977.0</td>\n <td>Southwest</td>\n </tr>\n <tr>\n <td>CIRCLE K 76 2708737</td>\n <td>{'latitude': '45.816</td>\n <td>98642</td>\n <td>RIDGEFIELD</td>\n <td>Southwest</td>\n <td>3</td>\n <td>2977.0</td>\n <td>Southwest</td>\n </tr>\n <tr>\n <td>FELKER ORCHARD INC</td>\n <td>{'latitude': '47.898</td>\n <td>98831</td>\n <td>MANSON</td>\n <td>Central</td>\n <td>8</td>\n <td>2956.0</td>\n <td>Central</td>\n </tr>\n <tr>\n <td>Automotive Services</td>\n <td>{'latitude': '45.637</td>\n <td>98660</td>\n <td>VANCOUVER</td>\n <td>Southwest</td>\n <td>3</td>\n <td>2977.0</td>\n <td>Southwest</td>\n </tr>\n <tr>\n <td>MCNARY FARM</td>\n <td>{'latitude': '45.966</td>\n <td>99346-9999</td>\n <td>PLYMOUTH</td>\n <td>Central</td>\n <td>4</td>\n <td>2955.0</td>\n <td>Central</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
{"cleanup_site_name":"ALBRICI PROPERTY","location":"{'latitude': '45.673","zipcode":"98665","city":"VANCOUVER","responsible_section":"Southwest",":@computed_region_fny7_vc3j":3,":@computed_region_x4ys_rtnd":2977.0,"region":"Southwest"} {"cleanup_site_name":"Willard Aldridge & A","location":"{'latitude': '47.418","zipcode":"98801","city":"WENATCHEE","responsible_section":"Central",":@computed_region_fny7_vc3j":8,":@computed_region_x4ys_rtnd":2956.0,"region":"Central"} {"cleanup_site_name":"Riverside Residentia","location":"{'latitude': '45.613","zipcode":"98661","city":"VANCOUVER","responsible_section":"Southwest",":@computed_region_fny7_vc3j":3,":@computed_region_x4ys_rtnd":2977.0,"region":"Southwest"} {"cleanup_site_name":"ABANDON TANK SITE","location":"{'latitude': '45.636","zipcode":"98660-2635","city":"VANCOUVER","responsible_section":"Southwest",":@computed_region_fny7_vc3j":3,":@computed_region_x4ys_rtnd":2977.0,"region":"Southwest"} {"cleanup_site_name":"CIRCLE K 76 2708737","location":"{'latitude': '45.816","zipcode":"98642","city":"RIDGEFIELD","responsible_section":"Southwest",":@computed_region_fny7_vc3j":3,":@computed_region_x4ys_rtnd":2977.0,"region":"Southwest"} {"cleanup_site_name":"FELKER ORCHARD INC","location":"{'latitude': '47.898","zipcode":"98831","city":"MANSON","responsible_section":"Central",":@computed_region_fny7_vc3j":8,":@computed_region_x4ys_rtnd":2956.0,"region":"Central"} {"cleanup_site_name":"Automotive Services ","location":"{'latitude': '45.637","zipcode":"98660","city":"VANCOUVER","responsible_section":"Southwest",":@computed_region_fny7_vc3j":3,":@computed_region_x4ys_rtnd":2977.0,"region":"Southwest"} {"cleanup_site_name":"MCNARY FARM","location":"{'latitude': '45.966","zipcode":"99346-9999","city":"PLYMOUTH","responsible_section":"Central",":@computed_region_fny7_vc3j":4,":@computed_region_x4ys_rtnd":2955.0,"region":"Central"}
tablereformat
2024-06-24T00:00:00
c42ef3e7297ebddb097e9aa4d5527dce29367f617c29bf7144de2633107ead00
data_analysis
[ "Please convert the Input Table from TSV format to JSON format. Please respond only with the table. \n Input Table: Promoter sequences\nCGGTAGTCCAGCTCGCGCCG\nAAGTCCGGACTCTAGGACTT\nGGATCTCTGTTCTTGGTCGA\nGGCGGGGCATTGAGTGGAAA\nTGATCGCTCCACGAAAGCCA\nTGTGTGGCGATCTGTAAACG\nAAATGTGCAATGCATTTTAT\nAGGCGCCGCGGGCCGGGAGG\nCTTGATCCGGAAAGGAAGGA\nGGCGGTGGGAGGCGGCGCCA\n \n Output: \n" ]
{"5255":{"Promoter sequences":"CGGTAGTCCAGCTCGCGCCG"},"23496":{"Promoter sequences":"AAGTCCGGACTCTAGGACTT"},"12972":{"Promoter sequences":"GGATCTCTGTTCTTGGTCGA"},"9545":{"Promoter sequences":"GGCGGGGCATTGAGTGGAAA"},"1762":{"Promoter sequences":"TGATCGCTCCACGAAAGCCA"},"14765":{"Promoter sequences":"TGTGTGGCGATCTGTAAACG"},"7305":{"Promoter sequences":"AAATGTGCAATGCATTTTAT"},"5247":{"Promoter sequences":"AGGCGCCGCGGGCCGGGAGG"},"29957":{"Promoter sequences":"CTTGATCCGGAAAGGAAGGA"},"8080":{"Promoter sequences":"GGCGGTGGGAGGCGGCGCCA"}}
tablereformat
2024-06-24T00:00:00
bfe58cf09204ef9dddeb7358323fbab09c078fbc88d022c2387e0eada4470849
data_analysis
[ "Please convert the Input Table from HTML format to JSON format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>:@computed_region_43wa_7qmu</th>\n <th>location</th>\n <th>case_</th>\n <th>date_of_occurrence</th>\n <th>block</th>\n <th>y_coordinate</th>\n <th>_primary_decsription</th>\n <th>latitude</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>47.0</td>\n <td>{'latitude': '41.707</td>\n <td>JG482108</td>\n <td>2023-10-28T13:00:00.</td>\n <td>103XX S EWING AVE</td>\n <td>1836919</td>\n <td>THEFT</td>\n <td>41.707238</td>\n </tr>\n <tr>\n <td>11.0</td>\n <td>{'latitude': '41.895</td>\n <td>JG496476</td>\n <td>2023-11-08T13:23:00.</td>\n <td>007XX N STATE ST</td>\n <td>1905475</td>\n <td>BATTERY</td>\n <td>41.895983</td>\n </tr>\n <tr>\n <td>15.0</td>\n <td>{'latitude': '41.768</td>\n <td>JG496126</td>\n <td>2023-11-08T01:00:00.</td>\n <td>068XX S TRIPP AVE</td>\n <td>1858947</td>\n <td>MOTOR VEHICLE THEFT</td>\n <td>41.768870</td>\n </tr>\n <tr>\n <td>1.0</td>\n <td>{'latitude': '41.826</td>\n <td>JG496997</td>\n <td>2023-11-08T20:20:00.</td>\n <td>037XX S WOLCOTT AVE</td>\n <td>1879970</td>\n <td>CRIMINAL TRESPASS</td>\n <td>41.826256</td>\n </tr>\n <tr>\n <td>25.0</td>\n <td>{'latitude': '41.932</td>\n <td>JG512901</td>\n <td>2023-11-21T14:00:00.</td>\n <td>007XX W DIVERSEY PKW</td>\n <td>1918825</td>\n <td>THEFT</td>\n <td>41.932739</td>\n </tr>\n <tr>\n <td>13.0</td>\n <td>{'latitude': '41.733</td>\n <td>JG499248</td>\n <td>2023-11-08T20:37:00.</td>\n <td>088XX S JUSTINE ST</td>\n <td>1846162</td>\n <td>DECEPTIVE PRACTICE</td>\n <td>41.733413</td>\n </tr>\n <tr>\n <td>20.0</td>\n <td>{'latitude': '41.946</td>\n <td>JG445052</td>\n <td>2023-09-30T10:01:00.</td>\n <td>029XX W ADDISON ST</td>\n <td>1923785</td>\n <td>THEFT</td>\n <td>41.946653</td>\n </tr>\n <tr>\n <td>33.0</td>\n <td>{'latitude': '41.802</td>\n <td>JG501047</td>\n <td>2023-11-08T15:00:00.</td>\n <td>008XX E HYDE PARK BL</td>\n <td>1871378</td>\n <td>BURGLARY</td>\n <td>41.802270</td>\n </tr>\n <tr>\n <td>33.0</td>\n <td>{'latitude': '41.757</td>\n <td>JG512493</td>\n <td>2023-11-21T03:00:00.</td>\n <td>075XX S KENWOOD AVE</td>\n <td>1855250</td>\n <td>MOTOR VEHICLE THEFT</td>\n <td>41.757924</td>\n </tr>\n <tr>\n <td>44.0</td>\n <td>{'latitude': '41.940</td>\n <td>JG496345</td>\n <td>2023-11-08T11:44:00.</td>\n <td>033XX N NORMANDY AVE</td>\n <td>1921379</td>\n <td>MOTOR VEHICLE THEFT</td>\n <td>41.940523</td>\n </tr>\n <tr>\n <td>30.0</td>\n <td>{'latitude': '41.742</td>\n <td>JG465660</td>\n <td>2023-10-15T20:00:00.</td>\n <td>083XX S KEDZIE AVE</td>\n <td>1849305</td>\n <td>THEFT</td>\n <td>41.742267</td>\n </tr>\n <tr>\n <td>40.0</td>\n <td>{'latitude': '41.935</td>\n <td>JG514854</td>\n <td>2023-11-21T12:00:00.</td>\n <td>029XX N ASHLAND AVE</td>\n <td>1919763</td>\n <td>CRIMINAL DAMAGE</td>\n <td>41.935433</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
{"808":{":@computed_region_43wa_7qmu":47.0,"location":"{'latitude': '41.707","case_":"JG482108","date_of_occurrence":"2023-10-28T13:00:00.","block":"103XX S EWING AVE","y_coordinate":1836919,"_primary_decsription":"THEFT","latitude":41.70723842},"83":{":@computed_region_43wa_7qmu":11.0,"location":"{'latitude': '41.895","case_":"JG496476","date_of_occurrence":"2023-11-08T13:23:00.","block":"007XX N STATE ST","y_coordinate":1905475,"_primary_decsription":"BATTERY","latitude":41.895982869},"643":{":@computed_region_43wa_7qmu":15.0,"location":"{'latitude': '41.768","case_":"JG496126","date_of_occurrence":"2023-11-08T01:00:00.","block":"068XX S TRIPP AVE","y_coordinate":1858947,"_primary_decsription":"MOTOR VEHICLE THEFT","latitude":41.768870183},"895":{":@computed_region_43wa_7qmu":1.0,"location":"{'latitude': '41.826","case_":"JG496997","date_of_occurrence":"2023-11-08T20:20:00.","block":"037XX S WOLCOTT AVE","y_coordinate":1879970,"_primary_decsription":"CRIMINAL TRESPASS","latitude":41.826255505},"536":{":@computed_region_43wa_7qmu":25.0,"location":"{'latitude': '41.932","case_":"JG512901","date_of_occurrence":"2023-11-21T14:00:00.","block":"007XX W DIVERSEY PKW","y_coordinate":1918825,"_primary_decsription":"THEFT","latitude":41.932738985},"874":{":@computed_region_43wa_7qmu":13.0,"location":"{'latitude': '41.733","case_":"JG499248","date_of_occurrence":"2023-11-08T20:37:00.","block":"088XX S JUSTINE ST","y_coordinate":1846162,"_primary_decsription":"DECEPTIVE PRACTICE","latitude":41.733413027},"55":{":@computed_region_43wa_7qmu":20.0,"location":"{'latitude': '41.946","case_":"JG445052","date_of_occurrence":"2023-09-30T10:01:00.","block":"029XX W ADDISON ST","y_coordinate":1923785,"_primary_decsription":"THEFT","latitude":41.946653043},"26":{":@computed_region_43wa_7qmu":33.0,"location":"{'latitude': '41.802","case_":"JG501047","date_of_occurrence":"2023-11-08T15:00:00.","block":"008XX E HYDE PARK BL","y_coordinate":1871378,"_primary_decsription":"BURGLARY","latitude":41.802269632},"990":{":@computed_region_43wa_7qmu":33.0,"location":"{'latitude': '41.757","case_":"JG512493","date_of_occurrence":"2023-11-21T03:00:00.","block":"075XX S KENWOOD AVE","y_coordinate":1855250,"_primary_decsription":"MOTOR VEHICLE THEFT","latitude":41.757924202},"78":{":@computed_region_43wa_7qmu":44.0,"location":"{'latitude': '41.940","case_":"JG496345","date_of_occurrence":"2023-11-08T11:44:00.","block":"033XX N NORMANDY AVE","y_coordinate":1921379,"_primary_decsription":"MOTOR VEHICLE THEFT","latitude":41.940522593},"60":{":@computed_region_43wa_7qmu":30.0,"location":"{'latitude': '41.742","case_":"JG465660","date_of_occurrence":"2023-10-15T20:00:00.","block":"083XX S KEDZIE AVE","y_coordinate":1849305,"_primary_decsription":"THEFT","latitude":41.742267488},"505":{":@computed_region_43wa_7qmu":40.0,"location":"{'latitude': '41.935","case_":"JG514854","date_of_occurrence":"2023-11-21T12:00:00.","block":"029XX N ASHLAND AVE","y_coordinate":1919763,"_primary_decsription":"CRIMINAL DAMAGE","latitude":41.935432921}}
tablereformat
2024-06-24T00:00:00
b64b2155d2e4e74cbb52dcb6f97298cbf28eef0159973600aecdc80a6c49c8df
data_analysis
[ "Please convert the Input Table from TSV format to JSONL format. Please respond only with the table. \n Input Table: provider_name\taddress1\taddress2\tcity\tcounty\tstate_code\tzip\tnational_drug_code\nHarmon City\t4727 W South Jordan \t\tSouth Jordan\tSalt Lake\tUT\t84009\t00069-1085-30\nKinney Drugs Inc. #9\t34 Route 30 N.\t\tBomoseen\tRutland\tVT\t5732\t00069-1101-20\nStop and Shop Store \t100 MACY STREET\t\tAmesbury\tEssex\tMA\t1913\t00069-1101-20\nSAFEWAY PHARMACY\t2785 Yulupa Ave\t\tSanta Rosa\tSonoma\tCA\t95405\t00069-1101-20\nSAFEWAY PHARMACY\t3383 BASS LAKE RD\t\tEl Dorado Hills\tEl Dorado\tCA\t95762\t00069-1085-30\nOSCO PHARMACY\t17930 WOLF RD\t\tOrland Park\tCook\tIL\t60467\t00069-1101-20\nOUR HOME PHARMACY\t2154 Moores Mill Roa\t\tAuburn\tLee\tAL\t36830\t00006-5055-06\n \n Output: \n" ]
{"provider_name":"Harmon City","address1":"4727 W South Jordan ","address2":null,"city":"South Jordan","county":"Salt Lake","state_code":"UT","zip":84009,"national_drug_code":"00069-1085-30"} {"provider_name":"Kinney Drugs Inc. #9","address1":"34 Route 30 N.","address2":null,"city":"Bomoseen","county":"Rutland","state_code":"VT","zip":5732,"national_drug_code":"00069-1101-20"} {"provider_name":"Stop and Shop Store ","address1":"100 MACY STREET","address2":null,"city":"Amesbury","county":"Essex","state_code":"MA","zip":1913,"national_drug_code":"00069-1101-20"} {"provider_name":"SAFEWAY PHARMACY","address1":"2785 Yulupa Ave","address2":null,"city":"Santa Rosa","county":"Sonoma","state_code":"CA","zip":95405,"national_drug_code":"00069-1101-20"} {"provider_name":"SAFEWAY PHARMACY","address1":"3383 BASS LAKE RD","address2":null,"city":"El Dorado Hills","county":"El Dorado","state_code":"CA","zip":95762,"national_drug_code":"00069-1085-30"} {"provider_name":"OSCO PHARMACY","address1":"17930 WOLF RD","address2":null,"city":"Orland Park","county":"Cook","state_code":"IL","zip":60467,"national_drug_code":"00069-1101-20"} {"provider_name":"OUR HOME PHARMACY","address1":"2154 Moores Mill Roa","address2":null,"city":"Auburn","county":"Lee","state_code":"AL","zip":36830,"national_drug_code":"00006-5055-06"}
tablereformat
2024-06-24T00:00:00
132dabf6ac92193bcc1b1cab0080ee5531ab45a959eefc1e5b3cbf57976bcf9a
data_analysis
[ "Please convert the Input Table from JSON format to HTML format. Please respond only with the table. \n Input Table: {\"3264\":{\"ticker\":600196,\"month\":\"2022\\/5\\/31\",\"trend\":1,\"REVS10\":1.0076,\"REVS20\":1.0301,\"REVS5\":1.0144,\"RSTR12\":-0.4453,\"RSTR24\":0.3802},\"3252\":{\"ticker\":600188,\"month\":\"2018\\/5\\/31\",\"trend\":0,\"REVS10\":0.902,\"REVS20\":0.9949,\"REVS5\":0.9876,\"RSTR12\":0.2531,\"RSTR24\":0.4153},\"9930\":{\"ticker\":600893,\"month\":\"2022\\/9\\/30\",\"trend\":1,\"REVS10\":0.8948,\"REVS20\":0.9143,\"REVS5\":0.8975,\"RSTR12\":-0.2299,\"RSTR24\":0.029},\"17332\":{\"ticker\":601992,\"month\":\"2021\\/8\\/31\",\"trend\":1,\"REVS10\":1.0423,\"REVS20\":1.0265,\"REVS5\":1.0037,\"RSTR12\":-0.1715,\"RSTR24\":-0.1578},\"16904\":{\"ticker\":601877,\"month\":\"2022\\/4\\/30\",\"trend\":1,\"REVS10\":0.9761,\"REVS20\":0.7925,\"REVS5\":1.0316,\"RSTR12\":-0.0138,\"RSTR24\":0.345},\"5731\":{\"ticker\":601939,\"month\":\"2020\\/3\\/31\",\"trend\":1,\"REVS10\":0.9829,\"REVS20\":0.9606,\"REVS5\":0.9953,\"RSTR12\":-0.0303,\"RSTR24\":-0.1032},\"10400\":{\"ticker\":601186,\"month\":\"2018\\/1\\/31\",\"trend\":0,\"REVS10\":1.0104,\"REVS20\":1.0262,\"REVS5\":0.9679,\"RSTR12\":-0.0372,\"RSTR24\":0.2458},\"237\":{\"ticker\":69,\"month\":\"2022\\/12\\/31\",\"trend\":1,\"REVS10\":0.9221,\"REVS20\":0.9535,\"REVS5\":0.978,\"RSTR12\":-0.2663,\"RSTR24\":-0.1871},\"11402\":{\"ticker\":601818,\"month\":\"2019\\/2\\/28\",\"trend\":0,\"REVS10\":1.0444,\"REVS20\":1.0874,\"REVS5\":1.0522,\"RSTR12\":0.0137,\"RSTR24\":0.092},\"928\":{\"ticker\":630,\"month\":\"2020\\/2\\/29\",\"trend\":0,\"REVS10\":0.9904,\"REVS20\":0.9321,\"REVS5\":0.9537,\"RSTR12\":-0.1195,\"RSTR24\":-0.2794}} \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>ticker</th> <th>month</th> <th>trend</th> <th>REVS10</th> <th>REVS20</th> <th>REVS5</th> <th>RSTR12</th> <th>RSTR24</th> </tr> </thead> <tbody> <tr> <td>600196</td> <td>2022/5/31</td> <td>1</td> <td>1.0076</td> <td>1.0301</td> <td>1.0144</td> <td>-0.4453</td> <td>0.3802</td> </tr> <tr> <td>600188</td> <td>2018/5/31</td> <td>0</td> <td>0.9020</td> <td>0.9949</td> <td>0.9876</td> <td>0.2531</td> <td>0.4153</td> </tr> <tr> <td>600893</td> <td>2022/9/30</td> <td>1</td> <td>0.8948</td> <td>0.9143</td> <td>0.8975</td> <td>-0.2299</td> <td>0.0290</td> </tr> <tr> <td>601992</td> <td>2021/8/31</td> <td>1</td> <td>1.0423</td> <td>1.0265</td> <td>1.0037</td> <td>-0.1715</td> <td>-0.1578</td> </tr> <tr> <td>601877</td> <td>2022/4/30</td> <td>1</td> <td>0.9761</td> <td>0.7925</td> <td>1.0316</td> <td>-0.0138</td> <td>0.3450</td> </tr> <tr> <td>601939</td> <td>2020/3/31</td> <td>1</td> <td>0.9829</td> <td>0.9606</td> <td>0.9953</td> <td>-0.0303</td> <td>-0.1032</td> </tr> <tr> <td>601186</td> <td>2018/1/31</td> <td>0</td> <td>1.0104</td> <td>1.0262</td> <td>0.9679</td> <td>-0.0372</td> <td>0.2458</td> </tr> <tr> <td>69</td> <td>2022/12/31</td> <td>1</td> <td>0.9221</td> <td>0.9535</td> <td>0.9780</td> <td>-0.2663</td> <td>-0.1871</td> </tr> <tr> <td>601818</td> <td>2019/2/28</td> <td>0</td> <td>1.0444</td> <td>1.0874</td> <td>1.0522</td> <td>0.0137</td> <td>0.0920</td> </tr> <tr> <td>630</td> <td>2020/2/29</td> <td>0</td> <td>0.9904</td> <td>0.9321</td> <td>0.9537</td> <td>-0.1195</td> <td>-0.2794</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
40af2768cabe32744e3b1efd2552edb077e2539a8f45808852e7d83147a82519
data_analysis
[ "Please convert the Input Table from CSV format to JSON format. Please respond only with the table. \n Input Table: Areas,freq_1,freq_2,freq_3,freq_4,freq_5,freq_6\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\n2.9031241357700805,1.0,0.0239186694370569,0.0817705502454882,0.0184121130082733,0.0232967707875751,0.0205981843912313\n5.935001077590961,1.0,0.1952383930229297,0.1581730415076839,0.0913619230392722,0.0831959065680687,0.055211315504823\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\n43.4120750441313,0.2285180552180082,0.0861248899911221,0.1400905334130899,0.0902471037071408,0.1635016246832906,0.1911773303133527\n \n Output: \n" ]
{"42245":{"Areas":0.0,"freq_1":0.0,"freq_2":0.0,"freq_3":0.0,"freq_4":0.0,"freq_5":0.0,"freq_6":0.0},"11487":{"Areas":2.9031241358,"freq_1":1.0,"freq_2":0.0239186694,"freq_3":0.0817705502,"freq_4":0.018412113,"freq_5":0.0232967708,"freq_6":0.0205981844},"7724":{"Areas":5.9350010776,"freq_1":1.0,"freq_2":0.195238393,"freq_3":0.1581730415,"freq_4":0.091361923,"freq_5":0.0831959066,"freq_6":0.0552113155},"12332":{"Areas":0.0,"freq_1":0.0,"freq_2":0.0,"freq_3":0.0,"freq_4":0.0,"freq_5":0.0,"freq_6":0.0},"63812":{"Areas":0.0,"freq_1":0.0,"freq_2":0.0,"freq_3":0.0,"freq_4":0.0,"freq_5":0.0,"freq_6":0.0},"73689":{"Areas":43.4120750441,"freq_1":0.2285180552,"freq_2":0.08612489,"freq_3":0.1400905334,"freq_4":0.0902471037,"freq_5":0.1635016247,"freq_6":0.1911773303}}
tablereformat
2024-06-24T00:00:00
ed3a1cf09c7eefe66d4775384c633a1bbc48f09a7d2257028362479f057d7e3e
data_analysis
[ "Please convert the Input Table from JSONL format to HTML format. Please respond only with the table. \n Input Table: {\"Promoter sequences\":\"GCTTCTTGGAGGAGGATGAG\"}\n{\"Promoter sequences\":\"GAAGTGGGCACAGGTGAGGG\"}\n{\"Promoter sequences\":\"ATGGCTCTCCACCCTTCACC\"}\n{\"Promoter sequences\":\"GAAGACACATCCTAACCTAC\"}\n{\"Promoter sequences\":\"ACCCCTCCCAGCCCTCTGCT\"}\n{\"Promoter sequences\":\"GACAATAAATTGGGGAAAAA\"}\n{\"Promoter sequences\":\"TAGCAACCTGTTCCTTGCAG\"}\n{\"Promoter sequences\":\"GAGATAAAAGTGGGGCAAGA\"}\n{\"Promoter sequences\":\"CCCCTGGACTCTGCCCCCAG\"}\n{\"Promoter sequences\":\"CCTCCCGGCTCCCTGCCTAG\"}\n \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>Promoter sequences</th> </tr> </thead> <tbody> <tr> <td>GCTTCTTGGAGGAGGATGAG</td> </tr> <tr> <td>GAAGTGGGCACAGGTGAGGG</td> </tr> <tr> <td>ATGGCTCTCCACCCTTCACC</td> </tr> <tr> <td>GAAGACACATCCTAACCTAC</td> </tr> <tr> <td>ACCCCTCCCAGCCCTCTGCT</td> </tr> <tr> <td>GACAATAAATTGGGGAAAAA</td> </tr> <tr> <td>TAGCAACCTGTTCCTTGCAG</td> </tr> <tr> <td>GAGATAAAAGTGGGGCAAGA</td> </tr> <tr> <td>CCCCTGGACTCTGCCCCCAG</td> </tr> <tr> <td>CCTCCCGGCTCCCTGCCTAG</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
0a03666dc72cf14a5cf569f517483315380edb796ac0394c3c204ced2e4a7428
data_analysis
[ "Please convert the Input Table from JSON format to CSV format. Please respond only with the table. \n Input Table: {\"209\":{\"id\":1940,\"project_code\":\"102-GY-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-27030\",\"asn_dn\":\"ASN-2638\",\"country\":\"Guyana\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"786\":{\"id\":7975,\"project_code\":\"114-UG-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-176\",\"asn_dn\":\"ASN-129\",\"country\":\"Uganda\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"602\":{\"id\":5976,\"project_code\":\"117-ET-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-28720\",\"asn_dn\":\"ASN-2579\",\"country\":\"Ethiopia\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"394\":{\"id\":3771,\"project_code\":\"116-ZA-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-41585\",\"asn_dn\":\"ASN-4386\",\"country\":\"South Africa\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"57\":{\"id\":532,\"project_code\":\"116-ZA-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-23500\",\"asn_dn\":\"ASN-2293\",\"country\":\"South Africa\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"657\":{\"id\":6563,\"project_code\":\"116-ZA-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-47051\",\"asn_dn\":\"ASN-4837\",\"country\":\"South Africa\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"867\":{\"id\":9032,\"project_code\":\"116-ZA-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-41040\",\"asn_dn\":\"ASN-3623\",\"country\":\"South Africa\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"457\":{\"id\":4457,\"project_code\":\"108-VN-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-23320\",\"asn_dn\":\"ASN-2275\",\"country\":\"Vietnam\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"637\":{\"id\":6415,\"project_code\":\"116-ZA-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-41582\",\"asn_dn\":\"ASN-4304\",\"country\":\"South Africa\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"},\"520\":{\"id\":5195,\"project_code\":\"116-ZA-T01\",\"pq\":\"Pre-PQ Process\",\"po_so\":\"SCMS-47051\",\"asn_dn\":\"ASN-4836\",\"country\":\"South Africa\",\"managed_by\":\"PMO - US\",\"fulfill_via\":\"Direct Drop\"}} \n Output: \n" ]
id,project_code,pq,po_so,asn_dn,country,managed_by,fulfill_via 1940,102-GY-T01,Pre-PQ Process,SCMS-27030,ASN-2638,Guyana,PMO - US,Direct Drop 7975,114-UG-T01,Pre-PQ Process,SCMS-176,ASN-129,Uganda,PMO - US,Direct Drop 5976,117-ET-T01,Pre-PQ Process,SCMS-28720,ASN-2579,Ethiopia,PMO - US,Direct Drop 3771,116-ZA-T01,Pre-PQ Process,SCMS-41585,ASN-4386,South Africa,PMO - US,Direct Drop 532,116-ZA-T01,Pre-PQ Process,SCMS-23500,ASN-2293,South Africa,PMO - US,Direct Drop 6563,116-ZA-T01,Pre-PQ Process,SCMS-47051,ASN-4837,South Africa,PMO - US,Direct Drop 9032,116-ZA-T01,Pre-PQ Process,SCMS-41040,ASN-3623,South Africa,PMO - US,Direct Drop 4457,108-VN-T01,Pre-PQ Process,SCMS-23320,ASN-2275,Vietnam,PMO - US,Direct Drop 6415,116-ZA-T01,Pre-PQ Process,SCMS-41582,ASN-4304,South Africa,PMO - US,Direct Drop 5195,116-ZA-T01,Pre-PQ Process,SCMS-47051,ASN-4836,South Africa,PMO - US,Direct Drop
tablereformat
2024-06-24T00:00:00
6a71a2fd132bae45c6ef2fc93d0bfcf3d4f71025db07ec88fed08ff83b4eca45
data_analysis
[ "Please convert the Input Table from CSV format to JSON format. Please respond only with the table. \n Input Table: age,job,marital,education,default,balance,housing,loan\n40,management,married,secondary,no,4025.0,yes,no\n50,services,married,secondary,no,1545.0,no,no\n59,management,married,tertiary,no,138.0,yes,yes\n40,services,married,secondary,no,10406.0,no,no\n25,admin.,single,secondary,no,105.0,no,yes\n52,blue-collar,married,primary,no,2977.0,no,no\n44,blue-collar,married,secondary,no,788.0,yes,no\n51,blue-collar,divorced,secondary,no,1069.0,yes,no\n46,blue-collar,single,secondary,no,338.0,yes,no\n \n Output: \n" ]
{"27436":{"age":40,"job":"management","marital":"married","education":"secondary","default":"no","balance":4025.0,"housing":"yes","loan":"no"},"23553":{"age":50,"job":"services","marital":"married","education":"secondary","default":"no","balance":1545.0,"housing":"no","loan":"no"},"1191":{"age":59,"job":"management","marital":"married","education":"tertiary","default":"no","balance":138.0,"housing":"yes","loan":"yes"},"26990":{"age":40,"job":"services","marital":"married","education":"secondary","default":"no","balance":10406.0,"housing":"no","loan":"no"},"15793":{"age":25,"job":"admin.","marital":"single","education":"secondary","default":"no","balance":105.0,"housing":"no","loan":"yes"},"21419":{"age":52,"job":"blue-collar","marital":"married","education":"primary","default":"no","balance":2977.0,"housing":"no","loan":"no"},"32518":{"age":44,"job":"blue-collar","marital":"married","education":"secondary","default":"no","balance":788.0,"housing":"yes","loan":"no"},"7902":{"age":51,"job":"blue-collar","marital":"divorced","education":"secondary","default":"no","balance":1069.0,"housing":"yes","loan":"no"},"33274":{"age":46,"job":"blue-collar","marital":"single","education":"secondary","default":"no","balance":338.0,"housing":"yes","loan":"no"}}
tablereformat
2024-06-24T00:00:00
c55626b8561ca43f0fdf11e24b2083c4d3180a83c87ea6171a159a1e82f1da54
data_analysis
[ "Please convert the Input Table from CSV format to HTML format. Please respond only with the table. \n Input Table: cedula,primernombre,primerapellido,segundoapellido,segundonombre\n20810705,LILIA,GOMEZ,DE VILLABON,\n30971467,MARIA,BUITRAGO,BARBOSA,LUDIVIA\n21200345,MARLENE,GONZALEZ,MOLINA,\n4399727,URIEL,RUEDA,CANO,DE JESUS\n30003620,MARIA,ALVAREZ,.,ADELA\n21203437,DENIS,RODRIGUEZ,BERNAL,\n3280381,JOSE,GUTIERREZ,SANCHEZ,CUSTODIO\n \n Output: \n" ]
<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th>cedula</th> <th>primernombre</th> <th>primerapellido</th> <th>segundoapellido</th> <th>segundonombre</th> </tr> </thead> <tbody> <tr> <td>20810705</td> <td>LILIA</td> <td>GOMEZ</td> <td>DE VILLABON</td> <td>NaN</td> </tr> <tr> <td>30971467</td> <td>MARIA</td> <td>BUITRAGO</td> <td>BARBOSA</td> <td>LUDIVIA</td> </tr> <tr> <td>21200345</td> <td>MARLENE</td> <td>GONZALEZ</td> <td>MOLINA</td> <td>NaN</td> </tr> <tr> <td>4399727</td> <td>URIEL</td> <td>RUEDA</td> <td>CANO</td> <td>DE JESUS</td> </tr> <tr> <td>30003620</td> <td>MARIA</td> <td>ALVAREZ</td> <td>.</td> <td>ADELA</td> </tr> <tr> <td>21203437</td> <td>DENIS</td> <td>RODRIGUEZ</td> <td>BERNAL</td> <td>NaN</td> </tr> <tr> <td>3280381</td> <td>JOSE</td> <td>GUTIERREZ</td> <td>SANCHEZ</td> <td>CUSTODIO</td> </tr> </tbody> </table>
tablereformat
2024-06-24T00:00:00
ed588c8250de9be2b31be0bc4c7820f3fa97c6084f822bce03d324f20d4c228d
data_analysis
[ "Please convert the Input Table from HTML format to JSONL format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>id</th>\n <th>report_number</th>\n <th>origin</th>\n <th>filer_id</th>\n <th>filer_name</th>\n <th>type</th>\n <th>funding_source_id</th>\n <th>funding_source</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>107243-26595</td>\n <td>107243</td>\n <td>FE</td>\n <td>26595</td>\n <td>STEVEN SCHULTZ</td>\n <td>Lobbyist</td>\n <td>26595</td>\n <td>STEVEN SCHULTZ (Self</td>\n </tr>\n <tr>\n <td>107333-18369</td>\n <td>107333</td>\n <td>FE</td>\n <td>17432</td>\n <td>CAPITOL STRATEGIES C</td>\n <td>Employer</td>\n <td>18369</td>\n <td>SPOKANE TRANSIT AUTH</td>\n </tr>\n <tr>\n <td>107287-19110</td>\n <td>107287</td>\n <td>FE</td>\n <td>17723</td>\n <td>THOMAS W KWIECIAK</td>\n <td>Employer</td>\n <td>19110</td>\n <td>NATL RIFLE ASSN OF A</td>\n </tr>\n <tr>\n <td>107220-18281</td>\n <td>107220</td>\n <td>FE</td>\n <td>17397</td>\n <td>PATRICK S BOSS (Casc</td>\n <td>Employer</td>\n <td>18281</td>\n <td>PORT OF GRANT CO DIS</td>\n </tr>\n <tr>\n <td>107377-17576</td>\n <td>107377</td>\n <td>FE</td>\n <td>17576</td>\n <td>ADAM GLICKMAN</td>\n <td>Lobbyist</td>\n <td>17576</td>\n <td>ADAM GLICKMAN (Self)</td>\n </tr>\n <tr>\n <td>107242-95286</td>\n <td>107242</td>\n <td>FE</td>\n <td>95285</td>\n <td>Adam Zarrin</td>\n <td>Employer</td>\n <td>95286</td>\n <td>LEUKEMIA &amp; LYMPHOMA</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
{"id":"107243-26595","report_number":107243,"origin":"FE","filer_id":26595,"filer_name":"STEVEN SCHULTZ","type":"Lobbyist","funding_source_id":26595,"funding_source":"STEVEN SCHULTZ (Self"} {"id":"107333-18369","report_number":107333,"origin":"FE","filer_id":17432,"filer_name":"CAPITOL STRATEGIES C","type":"Employer","funding_source_id":18369,"funding_source":"SPOKANE TRANSIT AUTH"} {"id":"107287-19110","report_number":107287,"origin":"FE","filer_id":17723,"filer_name":"THOMAS W KWIECIAK","type":"Employer","funding_source_id":19110,"funding_source":"NATL RIFLE ASSN OF A"} {"id":"107220-18281","report_number":107220,"origin":"FE","filer_id":17397,"filer_name":"PATRICK S BOSS (Casc","type":"Employer","funding_source_id":18281,"funding_source":"PORT OF GRANT CO DIS"} {"id":"107377-17576","report_number":107377,"origin":"FE","filer_id":17576,"filer_name":"ADAM GLICKMAN","type":"Lobbyist","funding_source_id":17576,"funding_source":"ADAM GLICKMAN (Self)"} {"id":"107242-95286","report_number":107242,"origin":"FE","filer_id":95285,"filer_name":"Adam Zarrin","type":"Employer","funding_source_id":95286,"funding_source":"LEUKEMIA & LYMPHOMA "}
tablereformat
2024-06-24T00:00:00
6204f00c8a38e299225434e2218dc1fbf65eb3040ed083a97c048e4f3b7dc2c8
data_analysis
[ "Please convert the Input Table from TSV format to JSONL format. Please respond only with the table. \n Input Table: id\tSex\tLength\tDiameter\tHeight\tWhole_weight\tShucked_weight\tViscera_weight\n648\tI\t0.46\t0.35\t0.12\t0.4885\t0.193\t0.105\n1277\tI\t0.48\t0.365\t0.1\t0.461\t0.2205\t0.0835\n2428\tF\t0.53\t0.385\t0.125\t0.6695\t0.289\t0.151\n1749\tM\t0.71\t0.575\t0.215\t2.009\t0.9895\t0.4475\n4153\tI\t0.43\t0.315\t0.115\t0.384\t0.1885\t0.0715\n705\tM\t0.415\t0.325\t0.14\t0.417\t0.1535\t0.1015\n3423\tF\t0.63\t0.475\t0.15\t1.172\t0.536\t0.254\n \n Output: \n" ]
{"id":648,"Sex":"I","Length":0.46,"Diameter":0.35,"Height":0.12,"Whole_weight":0.4885,"Shucked_weight":0.193,"Viscera_weight":0.105} {"id":1277,"Sex":"I","Length":0.48,"Diameter":0.365,"Height":0.1,"Whole_weight":0.461,"Shucked_weight":0.2205,"Viscera_weight":0.0835} {"id":2428,"Sex":"F","Length":0.53,"Diameter":0.385,"Height":0.125,"Whole_weight":0.6695,"Shucked_weight":0.289,"Viscera_weight":0.151} {"id":1749,"Sex":"M","Length":0.71,"Diameter":0.575,"Height":0.215,"Whole_weight":2.009,"Shucked_weight":0.9895,"Viscera_weight":0.4475} {"id":4153,"Sex":"I","Length":0.43,"Diameter":0.315,"Height":0.115,"Whole_weight":0.384,"Shucked_weight":0.1885,"Viscera_weight":0.0715} {"id":705,"Sex":"M","Length":0.415,"Diameter":0.325,"Height":0.14,"Whole_weight":0.417,"Shucked_weight":0.1535,"Viscera_weight":0.1015} {"id":3423,"Sex":"F","Length":0.63,"Diameter":0.475,"Height":0.15,"Whole_weight":1.172,"Shucked_weight":0.536,"Viscera_weight":0.254}
tablereformat
2024-06-24T00:00:00
4810de734ddf549ae44d69fe3717e2ad95593f88a0f7d72211f46cbdd22ad513
data_analysis
[ "Please convert the Input Table from JSON format to CSV format. Please respond only with the table. \n Input Table: {\"99\":{\"plan_strategy\":\"Regional Rail\",\"rtpid\":\"21-T11-100\",\"title\":\"Hovercraft | Service\",\"scope\":\"This program include\",\"open_period\":\"2021 - 2035\",\"funding_millions_yoe\":165,\"county\":\"Various\"},\"29\":{\"plan_strategy\":\"Interchanges and Bot\",\"rtpid\":\"21-T06-029\",\"title\":\"Corridor & Interchan\",\"scope\":\"This program include\",\"open_period\":\"2021 - 2035\",\"funding_millions_yoe\":239,\"county\":\"Sonoma\"},\"39\":{\"plan_strategy\":\"Interchanges and Bot\",\"rtpid\":\"21-T06-040\",\"title\":\"Corridor & Interchan\",\"scope\":\"This program include\",\"open_period\":\"2036 - 2050\",\"funding_millions_yoe\":86,\"county\":\"Santa Clara\"},\"44\":{\"plan_strategy\":\"Interchanges and Bot\",\"rtpid\":\"21-T06-045\",\"title\":\"Corridor & Interchan\",\"scope\":\"This program include\",\"open_period\":\"2036 - 2050\",\"funding_millions_yoe\":91,\"county\":\"Contra Costa\"},\"115\":{\"plan_strategy\":\"Regional Rail\",\"rtpid\":\"21-T11-201\",\"title\":\"Rail | New Station |\",\"scope\":\"This program include\",\"open_period\":\"2021 - 2035\",\"funding_millions_yoe\":14,\"county\":\"Sonoma\"},\"16\":{\"plan_strategy\":\"Interchanges and Bot\",\"rtpid\":\"21-T06-036\",\"title\":\"Corridor & Interchan\",\"scope\":\"This program include\",\"open_period\":\"2021 - 2035\",\"funding_millions_yoe\":23,\"county\":\"Solano\"}} \n Output: \n" ]
plan_strategy,rtpid,title,scope,open_period,funding_millions_yoe,county Regional Rail,21-T11-100,Hovercraft | Service,This program include,2021 - 2035,165,Various Interchanges and Bot,21-T06-029,Corridor & Interchan,This program include,2021 - 2035,239,Sonoma Interchanges and Bot,21-T06-040,Corridor & Interchan,This program include,2036 - 2050,86,Santa Clara Interchanges and Bot,21-T06-045,Corridor & Interchan,This program include,2036 - 2050,91,Contra Costa Regional Rail,21-T11-201,Rail | New Station |,This program include,2021 - 2035,14,Sonoma Interchanges and Bot,21-T06-036,Corridor & Interchan,This program include,2021 - 2035,23,Solano
tablereformat
2024-06-24T00:00:00
77765399a07884782f5a539ccb9e8820f5c15a090a666f59b21f804706ecadc9
data_analysis
[ "Please convert the Input Table from JSONL format to CSV format. Please respond only with the table. \n Input Table: {\"Unnamed: 0\":84,\"work_year\":2021,\"experience_level\":\"EX\",\"employment_type\":\"FT\",\"job_title\":\"Director of Data Sci\",\"salary\":130000,\"salary_currency\":\"EUR\",\"salary_in_usd\":153667}\n{\"Unnamed: 0\":365,\"work_year\":2022,\"experience_level\":\"SE\",\"employment_type\":\"FT\",\"job_title\":\"Data Scientist\",\"salary\":138600,\"salary_currency\":\"USD\",\"salary_in_usd\":138600}\n{\"Unnamed: 0\":496,\"work_year\":2022,\"experience_level\":\"EN\",\"employment_type\":\"FT\",\"job_title\":\"Data Engineer\",\"salary\":52800,\"salary_currency\":\"EUR\",\"salary_in_usd\":58035}\n{\"Unnamed: 0\":40,\"work_year\":2020,\"experience_level\":\"MI\",\"employment_type\":\"FT\",\"job_title\":\"Data Scientist\",\"salary\":45760,\"salary_currency\":\"USD\",\"salary_in_usd\":45760}\n{\"Unnamed: 0\":94,\"work_year\":2021,\"experience_level\":\"EN\",\"employment_type\":\"FT\",\"job_title\":\"Data Scientist\",\"salary\":2200000,\"salary_currency\":\"INR\",\"salary_in_usd\":29751}\n{\"Unnamed: 0\":311,\"work_year\":2022,\"experience_level\":\"MI\",\"employment_type\":\"FT\",\"job_title\":\"Data Scientist\",\"salary\":50000,\"salary_currency\":\"GBP\",\"salary_in_usd\":65438}\n{\"Unnamed: 0\":292,\"work_year\":2022,\"experience_level\":\"MI\",\"employment_type\":\"FT\",\"job_title\":\"Data Scientist\",\"salary\":130000,\"salary_currency\":\"USD\",\"salary_in_usd\":130000}\n{\"Unnamed: 0\":560,\"work_year\":2022,\"experience_level\":\"SE\",\"employment_type\":\"FT\",\"job_title\":\"Analytics Engineer\",\"salary\":205300,\"salary_currency\":\"USD\",\"salary_in_usd\":205300}\n \n Output: \n" ]
Unnamed: 0,work_year,experience_level,employment_type,job_title,salary,salary_currency,salary_in_usd 84,2021,EX,FT,Director of Data Sci,130000,EUR,153667 365,2022,SE,FT,Data Scientist,138600,USD,138600 496,2022,EN,FT,Data Engineer,52800,EUR,58035 40,2020,MI,FT,Data Scientist,45760,USD,45760 94,2021,EN,FT,Data Scientist,2200000,INR,29751 311,2022,MI,FT,Data Scientist,50000,GBP,65438 292,2022,MI,FT,Data Scientist,130000,USD,130000 560,2022,SE,FT,Analytics Engineer,205300,USD,205300
tablereformat
2024-06-24T00:00:00
b78c258e2cfd2954eb6ff290f39427d6270c69d57cc36e8a1c31839de39c885a
data_analysis
[ "Please convert the Input Table from HTML format to TSV format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>active</th>\n <th>vehicle_license_number</th>\n <th>name</th>\n <th>license_type</th>\n <th>expiration_date</th>\n <th>permit_license_number</th>\n <th>dmv_license_plate_number</th>\n <th>vehicle_vin_number</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>YES</td>\n <td>5428471</td>\n <td>AUGUSTINE,INDERYAS</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2026-04-03T00:00:00.</td>\n <td>AD901</td>\n <td>T797471C</td>\n <td>JTNBE46K473030973</td>\n </tr>\n <tr>\n <td>YES</td>\n <td>6035321</td>\n <td>RODRIGUEZ,JULIAN</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2025-06-30T00:00:00.</td>\n <td>AB172</td>\n <td>T119199C</td>\n <td>5TDADAB54RS000293</td>\n </tr>\n <tr>\n <td>YES</td>\n <td>6037476</td>\n <td>RODRIGUEZDIAZ,J,L</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2025-06-30T00:00:00.</td>\n <td>AD970</td>\n <td>T120985C</td>\n <td>1HGCY2F58PA051918</td>\n </tr>\n <tr>\n <td>YES</td>\n <td>6001467</td>\n <td>AMIN,MOHAMMED,N</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2024-07-29T00:00:00.</td>\n <td>AA492</td>\n <td>T106724C</td>\n <td>1FMCU4K32CKA37538</td>\n </tr>\n <tr>\n <td>YES</td>\n <td>6038054</td>\n <td>TURAKULOV,MEHROJ</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2025-06-30T00:00:00.</td>\n <td>AD935</td>\n <td>T119842C</td>\n <td>KNAGM4AD5G5092454</td>\n </tr>\n <tr>\n <td>YES</td>\n <td>5512440</td>\n <td>FAYYAZ,MUHAMMAD</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2025-10-09T00:00:00.</td>\n <td>AD646</td>\n <td>T641192C</td>\n <td>JTMRJREV7HD090829</td>\n </tr>\n <tr>\n <td>YES</td>\n <td>5608152</td>\n <td>SINGH,RAM</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2025-04-16T00:00:00.</td>\n <td>AB301</td>\n <td>T669464C</td>\n <td>4T1BD1FK1EU114595</td>\n </tr>\n <tr>\n <td>YES</td>\n <td>6064674</td>\n <td>SINGH,ARJUN</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2026-01-09T00:00:00.</td>\n <td>AD748</td>\n <td>T118272C</td>\n <td>4T1BK1EB5DU013873</td>\n </tr>\n <tr>\n <td>YES</td>\n <td>6034034</td>\n <td>ALMONTELORA,EZEQUIEL</td>\n <td>FOR HIRE VEHICLE</td>\n <td>2025-06-30T00:00:00.</td>\n <td>AA046</td>\n <td>T119200C</td>\n <td>KNDCB3LC4H5049067</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
active vehicle_license_number name license_type expiration_date permit_license_number dmv_license_plate_number vehicle_vin_number YES 5428471 AUGUSTINE,INDERYAS FOR HIRE VEHICLE 2026-04-03T00:00:00. AD901 T797471C JTNBE46K473030973 YES 6035321 RODRIGUEZ,JULIAN FOR HIRE VEHICLE 2025-06-30T00:00:00. AB172 T119199C 5TDADAB54RS000293 YES 6037476 RODRIGUEZDIAZ,J,L FOR HIRE VEHICLE 2025-06-30T00:00:00. AD970 T120985C 1HGCY2F58PA051918 YES 6001467 AMIN,MOHAMMED,N FOR HIRE VEHICLE 2024-07-29T00:00:00. AA492 T106724C 1FMCU4K32CKA37538 YES 6038054 TURAKULOV,MEHROJ FOR HIRE VEHICLE 2025-06-30T00:00:00. AD935 T119842C KNAGM4AD5G5092454 YES 5512440 FAYYAZ,MUHAMMAD FOR HIRE VEHICLE 2025-10-09T00:00:00. AD646 T641192C JTMRJREV7HD090829 YES 5608152 SINGH,RAM FOR HIRE VEHICLE 2025-04-16T00:00:00. AB301 T669464C 4T1BD1FK1EU114595 YES 6064674 SINGH,ARJUN FOR HIRE VEHICLE 2026-01-09T00:00:00. AD748 T118272C 4T1BK1EB5DU013873 YES 6034034 ALMONTELORA,EZEQUIEL FOR HIRE VEHICLE 2025-06-30T00:00:00. AA046 T119200C KNDCB3LC4H5049067
tablereformat
2024-06-24T00:00:00
26fbcb603a637ccd27d65387509e548e532334c5895fd56d7a9d531cc1b125fb
data_analysis
[ "Please convert the Input Table from HTML format to CSV format. Please respond only with the table. \n Input Table: <table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th>drugName</th>\n <th>url</th>\n <th>description</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <td>Hydrochlorothiazide</td>\n <td>https://www.drugs.co</td>\n <td>hydrochlorothiazide</td>\n </tr>\n <tr>\n <td>Geodon</td>\n <td>https://www.drugs.co</td>\n <td>geodon (ziprasidone)</td>\n </tr>\n <tr>\n <td>Novolin N</td>\n <td>https://www.drugs.co</td>\n <td>insulin is a hormone</td>\n </tr>\n <tr>\n <td>Prevacid</td>\n <td>https://www.drugs.co</td>\n <td>prevacid (lansoprazo</td>\n </tr>\n <tr>\n <td>Yupelri</td>\n <td>https://www.drugs.co</td>\n <td>yupelri (revefenacin</td>\n </tr>\n <tr>\n <td>Vimovo</td>\n <td>https://www.drugs.co</td>\n <td>vimovo contains a co</td>\n </tr>\n <tr>\n <td>Wellbutrin SR</td>\n <td>https://www.drugs.co</td>\n <td>wellbutrin sr is an</td>\n </tr>\n <tr>\n <td>Daliresp</td>\n <td>https://www.drugs.co</td>\n <td>daliresp (roflumilas</td>\n </tr>\n </tbody>\n</table> \n Output: \n" ]
drugName,url,description Hydrochlorothiazide ,https://www.drugs.co,hydrochlorothiazide Geodon,https://www.drugs.co,geodon (ziprasidone) Novolin N,https://www.drugs.co,insulin is a hormone Prevacid,https://www.drugs.co,prevacid (lansoprazo Yupelri,https://www.drugs.co,yupelri (revefenacin Vimovo,https://www.drugs.co,vimovo contains a co Wellbutrin SR,https://www.drugs.co,wellbutrin sr is an Daliresp,https://www.drugs.co,daliresp (roflumilas
tablereformat
2024-06-24T00:00:00
7c99777b2f4c5a9c88cc1f04d0345ac7b1e9dea2c7ac74b3fbf683e59bbf38f4
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Areas,freq_1,freq_2,freq_3,freq_4,freq_5,freq_6\\n11.46297225301157,0.750090555540225,1.0,0.0602354836548662,0.1838822583531753,0.0853333802592762,0.046024792724136\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n11.239817102920368,1.0,0.3186042752037932,0.1344797605815425,0.0786915134946252,0.0291092349742216,0.0462109552890391\\n14.225572256061094,0.3560941668350856,0.286557320911586,0.371644358207699,0.4729787680332255,0.3101131011117374,0.7074703432609266\\n9.865012036104266,1.0,0.2397341537732411,0.0729735395233181,0.0223524205245781,0.0287815331852048,0.0101898116116331\\n2.0757099662356238,0.9347092851067056,0.9400697206071236,1.0,0.9287615956012136,0.7355906053486795,0.5181680119786722\\n2.9067636626783804,1.0,0.1447597464229583,0.0480965667856174,0.0205783381644516,0.0171364415449829,0.0115787651851685\\n14.339409909977467,1.0,0.4250899142632741,0.1643871449873558,0.1020228497986892,0.041877682820639,0.0281545945678505\\n5.896129616650832,1.0,0.5067710275772761,0.1627128555154097,0.121165802190262,0.0619750338712106,0.0394802988626596\\n5.015217739188724,1.0,0.2137852227488661,0.0986187661484963,0.0384073657935623,0.022448891250256,0.0185346492464125\\n5.093743471481292,0.1329717423185582,0.1273505058545859,0.0590673294823516,0.0315282671087803,0.1411126511020878,0.2762081522183985\\n9.575908391909108,0.0937816299058494,0.0677546139020085,0.040494588488153,0.1130365447476912,0.0458418554377786,0.3351258627571026\\n12.43899843516728,1.0,0.2174001466603657,0.1215194187495121,0.0473273252051433,0.0278033476514428,0.021856868652518\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n \\n CSV Table B: 7raemdfhCtY,+xshpVlCqD4,QjH4XnyfWuI,vuFoAPLYFL8,Yz4/hhaFlUQ,NYLj0y6YLFA\\nNo,0.2710952149558612,6040452,0.1241531998855021,27.356016993528257,0\\nNo,0.0,6038888,0.0,0.0,0\\nNo,0.0,5941356,0.0,0.0,0\\nNo,0.0,6040452,0.0,0.0,0\\nNo,0.2134908745410948,5941356,0.057705281989179,21.995223196929345,0\\nSi,0.3283789206311447,5510456,0.100397995844769,14.12757778606885,0\\nSi,0.1982944056887898,6040452,0.0349326900415004,3.8333505006554778,0\\nSi,0.0,5510456,0.0,0.0,0\\nNo,0.0,6038888,0.0,0.0,0\\nNo,0.0,5026787,0.0,0.0,0\\nSi,0.2504480400031245,6040452,0.0446140544381391,6.936822133643822,0\\nNo,0.0,5510456,0.0,0.0,0\\nSi,0.2556343349867265,6038888,0.0652165586167969,29.10991285009921,0\\nSi,0.265151197362279,5941356,0.0603377249806183,15.422577029258743,0\\nNo,0.0,5510456,0.0,0.0,0\\n \\n Output: \\n" ]
{"freq_2": "+xshpVlCqD4", "Areas": "Yz4/hhaFlUQ", "freq_4": "vuFoAPLYFL8"}
tablejoin
2024-06-24T00:00:00
7d3b232a7df622492efaa9230b09fe5a5e45c12d35ed346a99b6ec201497a1e3
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: date,bundesland,gemeindeschluessel,anzahl_standorte,anzahl_meldebereiche,faelle_covid_aktuell,faelle_covid_aktuell_invasiv_beatmet,betten_frei,betten_belegt,betten_belegt_nur_erwachsen\\n2020-11-25,9,9762,1,1,7,3,4,14,14\\n2020-08-23,6,6440,5,5,1,0,20,76,76\\n2021-11-01,1,1056,2,2,1,1,3,34,34\\n2020-07-05,6,6633,3,3,0,0,7,28,28\\n2020-05-28,9,9678,2,2,1,0,2,6,6\\n2021-08-20,5,5124,5,7,9,4,18,131,122\\n2021-10-28,9,9576,1,1,0,0,0,5,5\\n2021-01-30,9,9672,4,4,3,2,3,37,37\\n2021-03-02,3,3101,5,7,8,4,19,113,99\\n2021-08-31,5,5762,5,6,2,1,9,26,24\\n2020-11-20,5,5911,6,8,18,12,33,166,153\\n2020-09-07,1,1003,2,2,1,0,110,107,107\\n2020-12-05,3,3354,1,1,0,0,0,6,6\\n2020-08-12,6,6435,4,7,0,0,25,65,55\\n2020-05-17,5,5962,8,8,6,3,55,71,71\\n2020-11-24,3,3455,2,2,2,1,14,23,23\\n \\n CSV Table B: T7gS0B9wuO8,5ArEgCtuDyM,IBOO7n66j2I,/8WN7SwQxtM,+TcFRhetc3o,XmI4BR0CDwY,xEEeWKcl26k,0bFLf6WxD8A,zSt62OHmjJ8\\n9777,24591000,Weak,gas,6040452,20,0,15.6466,5.0 out of 5 stars\\n12054,8334800,Weak,gas,6038888,55,0,15.6466,5.0 out of 5 stars\\n9462,9875400,Weak,gas,5941356,50,0,15.6466,5.0 out of 5 stars\\n15001,8338300,New,gas,6040452,25,0,15.6466,5.0 out of 5 stars\\n9362,8995500,Weak,gas,5941356,184,0,15.6466,5.0 out of 5 stars\\n3257,8564500,New,gas,5510456,22,0,15.6466,4.0 out of 5 stars\\n9572,8948500,New,gas,6040452,4,0,15.6466,5.0 out of 5 stars\\n13072,11859900,New,gas,5510456,33,0,15.6466,5.0 out of 5 stars\\n3153,16537400,Weak,gas,6038888,40,0,15.6466,5.0 out of 5 stars\\n15088,11010400,New,gas,5026787,16,0,15.6466,5.0 out of 5 stars\\n9371,7534000,New,gas,6040452,9,0,15.6466,5.0 out of 5 stars\\n8417,9818100,Weak,gas,5510456,19,0,15.6466,5.0 out of 5 stars\\n5711,9965000,Weak,gas,6038888,138,0,15.6466,5.0 out of 5 stars\\n7232,20254600,Good,gas,5941356,12,0,15.6466,5.0 out of 5 stars\\n9173,9989300,New,gas,5510456,22,0,15.6466,5.0 out of 5 stars\\n9676,12805200,Weak,gas,5026787,10,0,15.6466,5.0 out of 5 stars\\n6532,12652800,New,gas,5510456,47,0,15.6466,5.0 out of 5 stars\\n \\n Output: \\n" ]
{"betten_belegt": "XmI4BR0CDwY", "gemeindeschluessel": "T7gS0B9wuO8"}
tablejoin
2024-06-24T00:00:00
d89584191190995d5cb7307c938dbfb201e3af17ed7f666c2afae0fe2ad55985
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: hospital_pk,collection_week,state,ccn,hospital_name,address,city,zip,hospital_subtype,fips_code\\n131302,2020-04-05T00:00:00.,ID,131302.0,NORTH CANYON MEDICAL,267 NORTH CANYON DR,GOODING,83330,Critical Access Hosp,16047.0\\n420023,2020-05-10T00:00:00.,SC,420023.0,ST FRANCIS-DOWNTOWN,ONE ST FRANCIS DR,GREENVILLE,29601,Short Term,45045.0\\n030016,2020-05-10T00:00:00.,AZ,30016.0,BANNER CASA GRANDE M,1800 EAST FLORENCE B,CASA GRANDE,85122,Short Term,4021.0\\n452019,2020-05-17T00:00:00.,TX,452019.0,KINDRED HOSPITAL FOR,1802 HIGHWAY 157 NOR,MANSFIELD,76063,Long Term,48439.0\\n400005,2020-05-31T00:00:00.,PR,400005.0,HIMA SAN PABLO HUMAC,CALLE FONT MARTELO #,HUMACAO,791,Short Term,72069.0\\n650003,2020-06-21T00:00:00.,GU,650003.0,GUAM REGIONAL MEDICA,133 ROUTE 3,DEDEDO,96929,Short Term,66010.0\\n440183,2020-05-17T00:00:00.,TN,440183.0,ST FRANCIS HOSPITAL,5959 PARK AVE,MEMPHIS,38119,Short Term,47157.0\\n490060,2020-06-07T00:00:00.,VA,490060.0,CLINCH VALLEY MEDICA,6801 GOVERNOR GC PER,RICHLANDS,24641,Short Term,51185.0\\n110226,2020-06-28T00:00:00.,GA,110226.0,EMORY HILLANDALE HOS,2801 DEKALB MEDICAL ,LITHONIA,30058,Short Term,13089.0\\n410012,2020-06-21T00:00:00.,RI,410012.0,THE MIRIAM HOSPITAL,164 SUMMIT AVENUE,PROVIDENCE,2906,Short Term,44007.0\\n010095,2020-05-17T00:00:00.,AL,10095.0,HALE COUNTY HOSPITAL,508 GREEN STREET,GREENSBORO,36744,Short Term,1065.0\\n231305,2020-05-31T00:00:00.,MI,231305.0,ASCENSION STANDISH H,805 W CEDAR ST,STANDISH,48658,Critical Access Hosp,26011.0\\n360029,2020-05-31T00:00:00.,OH,360029.0,WOOD COUNTY HOSPITAL,950 WEST WOOSTER STR,BOWLING GREEN,43402,Short Term,39173.0\\n310040,2020-08-02T00:00:00.,NJ,310040.0,CAREPOINT HEALTH-HOB,308 WILLOW AVE,HOBOKEN,7030,Short Term,34017.0\\n140289,2020-05-24T00:00:00.,IL,140289.0,ANDERSON HOSPITAL,6800 STATE ROUTE 162,MARYVILLE,62062,Short Term,17119.0\\n140122,2020-03-29T00:00:00.,IL,140122.0,UCHICAGO MEDICINE AD,120 NORTH OAK ST,HINSDALE,60521,Short Term,17043.0\\n192037,2020-05-10T00:00:00.,LA,192037.0,HOUMA - AMG SPECIALT,629 DUNN STREET,HOUMA,70360,Long Term,22109.0\\n140100,2020-04-12T00:00:00.,IL,140100.0,MIDWESTERN REGION ME,2520 ELISHA AVENUE,ZION,60099,Short Term,17097.0\\n010150,2020-04-19T00:00:00.,AL,10150.0,REGIONAL MEDICAL CEN,29 L V STABLER DRIVE,GREENVILLE,36037,Short Term,1013.0\\n \\n CSV Table B: LB1c5bVtloU,NWoi+UEeAUY,cOXVTPLBCRY,eaRWRFfT5Wg,am9yrWhMHrw,RKRCNpVVdoc\\n6040452,0,15.6466,55422,3300 OAKDALE NORTH,Short Term\\n6038888,1,15.6466,68632,372 SOUTH 9TH STREET,Critical Access Hosp\\n5941356,2,15.6466,30286,801 W GORDON STREET,Short Term\\n6040452,3,15.6466,51401,311 SOUTH CLARK STRE,Short Term\\n5941356,4,15.6466,60451,1900 SILVER CROSS BL,Short Term\\n5510456,5,15.6466,46011,1515 N MADISON AVE,Short Term\\n6040452,6,15.6466,82443,150 EAST ARAPAHOE,Critical Access Hosp\\n5510456,7,15.6466,63368,2 PROGRESS POINT PKW,Short Term\\n6038888,8,15.6466,97845,170 FORD ROAD,Critical Access Hosp\\n5026787,9,15.6466,70633,110 WEST 4TH STREET,Critical Access Hosp\\n6040452,10,15.6466,70128,14500 HAYNE BLVD,Long Term\\n5510456,11,15.6466,79410,3815 20TH STREET,Long Term\\n6038888,12,15.6466,97225,9205 SW BARNES ROAD,Short Term\\n5941356,13,15.6466,47882,2200 N SECTION ST,Critical Access Hosp\\n5510456,14,15.6466,48202,2799 W GRAND BLVD,Short Term\\n5026787,15,15.6466,79347,708 S 1ST ST,Critical Access Hosp\\n5510456,16,15.6466,15801,100 HOSPITAL AVENUE,Short Term\\n5026787,17,15.6466,19301,255 WEST LANCASTER A,Short Term\\n5510456,18,15.6466,47804,1606 N SEVENTH ST,Short Term\\n \\n Output: \\n" ]
{"zip": "eaRWRFfT5Wg", "address": "am9yrWhMHrw", "hospital_subtype": "RKRCNpVVdoc"}
tablejoin
2024-06-24T00:00:00
1620e3381c6b9ba1ff0bcde15d816ec23ce445e1de6ed45de56ca41b0d1ae855
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Areas,freq_1,freq_2,freq_3,freq_4,freq_5,freq_6\\n5.933795753838489,1.0,0.7714353152956073,0.3375919869424647,0.0704448788641532,0.0107929607876282,0.0267687337606832\\n1.5210910200051493,1.0,0.3352216459590461,0.3142629045582596,0.018591929252257,0.0044317931629377,0.0180898247588335\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n1.6806327718556786,1.0,0.2886022195535446,0.1519876382827813,0.0955270177197378,0.0582274733294353,0.0120363467931941\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n3.394541372160921,0.9340198828403428,0.5170177427626574,0.8907295186595751,0.6248519995457857,0.4801956382727493,0.0963058220609996\\n1.940443897590438,1.0,0.0168048360419492,0.0684236444875642,0.0197865184978094,0.0085870714109561,0.0218420918462181\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n22.69973176183243,1.0,0.2635890581296524,0.1015738531735589,0.0557092844099098,0.0389717755071762,0.0268118043445155\\n15.72102675863944,1.0,0.2534177765079918,0.1213851367645493,0.0758989580007738,0.0497306692526718,0.0423569503878933\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n16.790685004304716,1.0,0.4596285598249906,0.2470266743171786,0.159609995246162,0.0683835858311823,0.0611051507365258\\n3.775196155630213,1.0,0.1484267571813163,0.0838537815456624,0.0467573958130329,0.0290824998529619,0.0202236843754584\\n \\n CSV Table B: 9DjQ3tK+uag,ei1O4ueH08o,a6oKqAbhiYE,oZa6HchyMZU,KaFTwefModI\\n0.0889692177421741,4.451112936702725,gas,1.0,0.0518831658900293\\n0.0,0.0,gas,0.0,0.0\\n0.0,0.0,gas,0.0,0.0\\n0.3500152338519772,2.6029018246824216,gas,0.5115910674487147,0.4856065717300028\\n0.0312477623708865,6.100652645212125,gas,1.0,0.0280783737865971\\n0.0,0.0,gas,0.0,0.0\\n0.0,0.0,gas,0.0,0.0\\n0.1195854319548732,5.928007798057385,gas,1.0,0.0520140122427527\\n0.4863107106367197,3.990970350783068,gas,1.0,0.3519195684437978\\n0.0,0.0,gas,0.0,0.0\\n0.1889284571653062,8.889283224092921,gas,1.0,0.0781596355026045\\n0.0,0.0,gas,0.0,0.0\\n0.0,0.0,gas,0.0,0.0\\n0.0879670614404105,4.20557923909491,gas,1.0,0.0952474046083429\\n0.0,0.0,gas,0.0,0.0\\n \\n Output: \\n" ]
{"freq_1": "oZa6HchyMZU", "Areas": "ei1O4ueH08o", "freq_3": "9DjQ3tK+uag", "freq_4": "KaFTwefModI"}
tablejoin
2024-06-24T00:00:00
01fc14e123214c67cbf235824d1ec952a825d5f78464ecc18fb9609c2781f50c
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: email,label\\nAct now! Limited-tim,spam\\nUpgrade to our premi,ham\\nThank you for subscr,ham\\nYour order has been ,ham\\nWe're excited to sha,ham\\nURGENT: Your account,spam\\nWe've extended our s,ham\\nYou've been selected,spam\\nYour account has bee,spam\\nUnlock exclusive dis,spam\\n \\n CSV Table B: lG1K/C5s5Ww,t8DtGa8xUVw\\nham,0\\nham,0\\nham,0\\nham,0\\nham,0\\nham,0\\nspam,0\\nham,0\\nham,0\\nham,0\\nham,0\\n \\n Output: \\n" ]
{"label": "lG1K/C5s5Ww"}
tablejoin
2024-06-24T00:00:00
490dfdc0383f199c870aa7710499c4081c35ff3545415dab3904f64e7526a809
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: name,id,nametype,recclass,mass,fall,year,reclat,reclong,geolocation\\nRepeev Khutor,22590,Valid,\"Iron, IIF\",7000.0,Fell,1933-01-01T00:00:00.,48.6,45.66667,\"{\\'latitude\\': \\'48.6\\',\"\\nKhmelevka,12297,Valid,L5,6109.0,Fell,1929-01-01T00:00:00.,56.75,75.33333,{\\'latitude\\': \\'56.75\\'\\nRichland Springs,22602,Valid,OC,1900.0,Fell,1980-01-01T00:00:00.,31.25,-99.03333,{\\'latitude\\': \\'31.25\\'\\nLichtenberg,14646,Valid,H6,4000.0,Fell,1973-01-01T00:00:00.,-26.15,26.18333,{\\'latitude\\': \\'-26.15\\nDjati-Pengilon,7652,Valid,H6,166000.0,Fell,1884-01-01T00:00:00.,-7.5,111.5,\"{\\'latitude\\': \\'-7.5\\',\"\\nJohnstown,12198,Valid,Diogenite,40300.0,Fell,1924-01-01T00:00:00.,40.35,-104.9,{\\'latitude\\': \\'40.35\\'\\nDanville,5514,Valid,L6,2000.0,Fell,1868-01-01T00:00:00.,34.4,-87.06667,\"{\\'latitude\\': \\'34.4\\',\"\\nDesuri,6693,Valid,H6,25400.0,Fell,1962-01-01T00:00:00.,25.73333,73.61667,{\\'latitude\\': \\'25.733\\nMyhee Caunta,16887,Valid,OC,,Fell,1842-01-01T00:00:00.,23.05,72.63333,{\\'latitude\\': \\'23.05\\'\\nGlanerbrug,10923,Valid,L/LL5,670.0,Fell,1990-01-01T00:00:00.,52.2,6.86667,\"{\\'latitude\\': \\'52.2\\',\"\\nElenovka,7824,Valid,L5,54640.0,Fell,1951-01-01T00:00:00.,47.83333,37.66667,{\\'latitude\\': \\'47.833\\n \\n CSV Table B: +wt5tR9hUmk,qYGU6k7IF84,SfVC0olx/OE,dpKqmiM3LcE,NljmnVvMvfc,q4yxeqSsc3o,SeflMNbyB9c\\n2405.0,gas,24591000,1955-01-01T00:00:00.,Fell,5.0 out of 5 stars,Weak\\n650.0,gas,8334800,1868-01-01T00:00:00.,Fell,5.0 out of 5 stars,Weak\\n737.6,gas,9875400,1962-01-01T00:00:00.,Fell,5.0 out of 5 stars,Weak\\n61.4,gas,8338300,1981-01-01T00:00:00.,Fell,5.0 out of 5 stars,New\\n85000.0,gas,8995500,1961-01-01T00:00:00.,Fell,5.0 out of 5 stars,Weak\\n9.6,gas,8564500,2003-01-01T00:00:00.,Found,4.0 out of 5 stars,New\\n350.0,gas,8948500,1908-01-01T00:00:00.,Fell,5.0 out of 5 stars,New\\n1393.0,gas,11859900,1883-01-01T00:00:00.,Fell,5.0 out of 5 stars,New\\n680.5,gas,16537400,1998-01-01T00:00:00.,Fell,5.0 out of 5 stars,Weak\\n22.0,gas,11010400,1866-01-01T00:00:00.,Fell,5.0 out of 5 stars,New\\n0.5,gas,7534000,1814-01-01T00:00:00.,Fell,5.0 out of 5 stars,New\\n \\n Output: \\n" ]
{"mass": "+wt5tR9hUmk", "fall": "NljmnVvMvfc", "year": "dpKqmiM3LcE"}
tablejoin
2024-06-24T00:00:00
0764131eaf30bb8af36ad749f144da01c0113b1cee00092dde2919287df2ba78
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Period\\\\Unit:,[Australian dollar ],[Bulgarian lev ],[Brazilian real ],[Canadian dollar ],[Swiss franc ],[Chinese yuan renminbi ],[Cypriot pound ],[Czech koruna ],[Danish krone ]\\n2012-10-11,1.2573,1.9558,2.6339,1.2645,1.2087,8.1086,,24.940,7.4588\\n2001-05-25,1.6485,1.9461,2.0210,1.3240,1.5272,7.1108,0.57697,34.288,7.4592\\n2009-11-30,1.6452,1.9558,2.6251,1.5882,1.5071,10.2564,,26.135,7.4424\\n2007-08-17,1.7213,1.9558,2.7736,1.4416,1.6245,10.2184,0.58420,27.663,7.4409\\n2005-06-16,1.5738,1.9560,2.9448,1.4984,1.5395,10.0270,0.57420,29.960,7.4429\\n2023-08-14,1.6853,1.9558,5.3764,1.47,0.9608,7.9356,,24.038,7.4515\\n2021-05-24,1.5804,1.9558,6.5299,1.4731,1.0957,7.8487,,25.424,7.4364\\n2011-04-12,1.3783,1.9558,2.2859,1.3864,1.3017,9.4638,,24.448,7.4584\\n2015-09-18,1.5709,1.9558,4.4370,1.4876,1.0913,7.2674,,27.071,7.4612\\n2022-05-16,1.5057,1.9558,5.2819,1.3473,1.0479,7.0786,,24.710,7.4418\\n \\n CSV Table B: crjCpvL6IHM,PzdYfZWVuZ8,NxnXOP1axWA,qQ/ysRVsisg,bG37FIQSUl4,ZTaHTGeeVq0,GChDi7tNjcY,sCAriUO7mec\\n2014-01-07,1.2367,6040452,5.0 out of 5 stars,gas,24591000,27.454,3.2241\\n2021-04-14,1.1033,6038888,5.0 out of 5 stars,gas,8334800,25.929,6.8189\\n2024-02-09,0.9432,5941356,5.0 out of 5 stars,gas,9875400,25.172,5.3637\\n1999-07-05,1.6055,6040452,5.0 out of 5 stars,gas,8338300,36.188,\\n1999-02-25,1.5905,5941356,5.0 out of 5 stars,gas,8995500,37.994,\\n1999-05-14,1.6020,5510456,4.0 out of 5 stars,gas,8564500,37.627,\\n2012-09-19,1.2095,6040452,5.0 out of 5 stars,gas,8948500,24.870,2.6317\\n2018-10-25,1.1407,5510456,5.0 out of 5 stars,gas,11859900,25.831,4.2357\\n2024-02-20,0.9526,6038888,5.0 out of 5 stars,gas,16537400,25.429,5.3521\\n2001-03-14,1.5361,5026787,5.0 out of 5 stars,gas,11010400,34.608,1.9048\\n \\n Output: \\n" ]
{"[Czech koruna ]": "GChDi7tNjcY", "[Swiss franc ]": "PzdYfZWVuZ8", "Period\\Unit:": "crjCpvL6IHM", "[Brazilian real ]": "sCAriUO7mec"}
tablejoin
2024-06-24T00:00:00
55d610b0b74c049e9664df825f1bffcb7999fffc0576ff3317960a2124c3feaf
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Unnamed: 0,military_base_name,coordinates,longtitudes,latitudes,description\\n231,Warehouses,\"36.192135119525,51.7\",36.192135119525,51.76504015277498,military unit 55443-\\n2549,\"FGKU plant \"\"Zaliv\"\", \",\"91.2538259396279,53.\",91.2538259396279,53.84058923722024,\\n2268,Training Center for ,\"37.45257182147071,55\",37.45257182147071,55.65068030560189,A special object of \\n2463,Foreign Intelligence,\"37.51818966901558,55\",37.51818966901558,55.58494050230941,\\n2904,Testing Facility of ,\"30.17821336359249,60\",30.17821336359249,60.29493749739285,Testing of missiles \\n2566,\"FGKU plant \"\"Argun\"\", \",\"114.3215040279572,51\",114.3215040279572,51.61993889490242,\\n974,122nd Missile Regime,\"45.38931092844241,52\",45.38931092844241,52.23762486615308,\"military unit 77980,\"\\n1221,874th Radio-Technica,\"40.42184468866319,56\",40.42184468866319,56.13374562694942,military unit 30790\\n443,Warehouse,\"83.06531660551912,54\",83.06531660551912,54.95831270373129,military unit 58661-\\n2769,Training Ground,\"33.17734347037145,68\",33.17734347037145,68.88951166395577,\\n2621,/A Combined Arms Aca,\"37.6956668243265,55.\",37.6956668243265,55.76136846272302,\\n1746,280th Guards Motor R,\"22.2162231483651,54.\",22.2162231483651,54.59815334275081,\\n2696,Transmitting Radio C,\"40.13394840314977,62\",40.13394840314977,62.65320112079713,\\n1650,332nd Radio-Technica,\"40.68273814029152,64\",40.68273814029152,64.5187161106319,military unit 21514\\n2666,Z/4,\"143.0899635435795,59\",143.0899635435795,59.41749468741156,\\n2412,94th Internal Troops,\"43.31647007301511,54\",43.31647007301511,54.9363508702557,military unit 3274\\n2732,Training Grounds,\"36.92967872777752,55\",36.92967872777752,55.54215358750233,\\n \\n CSV Table B: dldBxBN4tl4,SmRhS/d2xpk,gVRuuM0qimI,7SxcDOM+98w,VP8coLynuXw\\n44.51916101735122,6040452,33.48334624839457,0,\\n51.82107969463786,6038888,107.6915756165818,0,\\n61.83338956320217,5941356,34.25154208925353,0,military unit 18558\\n55.8398933314324,6040452,37.56263109395489,0,Estabilished in Janu\\n56.19537331447595,5941356,37.04376605026997,0,military unit 92154\\n43.75156070078539,5510456,44.01921733219185,0,\"military unit 31681,\"\\n49.9425896490698,6040452,40.4966289477541,0,military unit 83833\\n48.68547115904807,5510456,45.72473406052717,0,\\n67.66637512688602,6038888,49.037423858874,0,Designed to detect a\\n51.5646535131477,5026787,113.0394034094085,0,military unit 48271 \\n55.47150518695323,6040452,28.78653481318823,0,military unit 32404\\n47.21956872393976,5510456,39.70363102317334,0,\\n46.3954054309925,6038888,47.90753819956586,0,\"MiG-29UBM, MiG-29SMT\"\\n52.5842238897004,5941356,39.56394893283026,0,military unit 5961\\n50.70253121855274,5510456,136.7369473000318,0,military unit 47127\\n56.46296735538946,5026787,48.14977296610531,0,military unit 58661-\\n51.59114083272477,5510456,39.09266975663168,0,\"military unit 51025,\"\\n43.9348278717269,5026787,131.8872930091488,0,\\n \\n Output: \\n" ]
{"latitudes": "dldBxBN4tl4", "description": "VP8coLynuXw", "longtitudes": "gVRuuM0qimI"}
tablejoin
2024-06-24T00:00:00
9d53b3ca366bedc7b149a5d41a4dc5c52cd76f1989a0cb6020d304fef6eb8d8d
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: valor,unidad,vigenciadesde,vigenciahasta\\n3843.59,COP,2020-10-15T00:00:00.,2020-10-15T00:00:00.\\n3997.09,COP,2021-12-24T00:00:00.,2021-12-24T00:00:00.\\n3450.74,COP,2021-01-06T00:00:00.,2021-01-06T00:00:00.\\n4003.95,COP,2022-01-20T00:00:00.,2022-01-20T00:00:00.\\n3993.53,COP,2023-09-13T00:00:00.,2023-09-13T00:00:00.\\n3639.12,COP,2021-04-22T00:00:00.,2021-04-22T00:00:00.\\n3784.44,COP,2021-10-30T00:00:00.,2021-11-02T00:00:00.\\n3927.25,COP,2022-02-19T00:00:00.,2022-02-22T00:00:00.\\n4039.31,COP,2022-01-07T00:00:00.,2022-01-07T00:00:00.\\n3905.95,COP,2023-09-19T00:00:00.,2023-09-19T00:00:00.\\n4506.49,COP,2023-05-16T00:00:00.,2023-05-16T00:00:00.\\n3827.27,COP,2020-08-22T00:00:00.,2020-08-24T00:00:00.\\n3743.79,COP,2020-05-28T00:00:00.,2020-05-28T00:00:00.\\n \\n CSV Table B: e8EOCOtc2tE,92E9ya41vLI,Qiz4gNNSkjU\\nCOP,2023-01-20T00:00:00.,0\\nCOP,2022-12-23T00:00:00.,0\\nCOP,2023-07-06T00:00:00.,0\\nCOP,2023-05-15T00:00:00.,0\\nCOP,2021-11-18T00:00:00.,0\\nCOP,2021-08-25T00:00:00.,0\\nCOP,2022-10-03T00:00:00.,0\\nCOP,2022-01-27T00:00:00.,0\\nCOP,2022-08-18T00:00:00.,0\\nCOP,2022-03-24T00:00:00.,0\\nCOP,2021-04-14T00:00:00.,0\\nCOP,2023-06-05T00:00:00.,0\\nCOP,2021-03-26T00:00:00.,0\\nCOP,2023-08-14T00:00:00.,0\\n \\n Output: \\n" ]
{"vigenciahasta": "92E9ya41vLI", "unidad": "e8EOCOtc2tE"}
tablejoin
2024-06-24T00:00:00
d4b2efd567053821eedf1ea3f759d4948f50264b94bd6ff37b18bc92e79d4fc1
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: DeviceTimeStamp,WL1,WL2,WL3,VAL1,VAL2,VAL3,RVAL1,RVAL2,RVAL3\\n2019-10-04T15:30,34.3,24.5,32.1,34.9,24.8,32.2,5.9,3.8,0.0032\\n2019-09-13T19:15,32.1,29.3,36.5,32.6,29.3,36.7,5.5,0.7,0.0037\\n2019-07-14T15:30,15.8,9.9,16.3,15.9,10.2,17.4,1.8,2.7,0.0059\\n2020-02-15T15:00,22.6,12.2,22.8,22.7,12.5,23.9,1.6,2.7,0.0072\\n2019-07-16T21:30,30.5,17.9,23.0,30.6,18.2,23.8,1.6,3.0,0.0058\\n2020-01-21T04:45,7.5,3.2,8.0,7.5,3.5,8.2,0.0,1.4,0.0016\\n2019-10-12T02:15,16.3,16.0,22.4,16.3,16.2,22.7,1.3,2.3,0.0041\\n2019-07-17T21:45,27.1,21.7,35.6,27.1,21.8,35.9,0.5,1.8,0.0052\\n2020-02-14T18:32,25.6,23.3,33.1,25.7,23.4,33.2,2.0,1.1,0.0031\\n2019-10-13T09:30,11.5,8.4,13.0,11.6,8.6,13.5,1.4,1.9,0.0036\\n2019-07-21T03:00,21.1,14.4,15.5,21.1,14.9,16.0,0.5,3.6,0.0042\\n2019-07-17T11:30,28.1,33.4,21.8,28.2,33.8,22.4,2.5,5.3,0.0051\\n2019-09-29T02:30,13.9,10.6,17.5,14.1,10.8,17.5,2.8,1.8,0.0003\\n2019-10-25T03:15,9.1,8.9,12.6,9.1,9.0,12.8,0.0,1.4,0.0019\\n2019-11-16T14:45,24.8,17.4,24.9,24.9,17.6,25.7,1.8,2.6,0.0061\\n2019-08-12T23:15,18.3,23.5,29.8,18.3,23.8,30.0,1.0,3.8,0.0038\\n2019-11-12T00:15,9.9,7.3,13.0,9.9,7.5,13.1,0.0,1.7,0.0018\\n2020-02-22T12:00,20.5,15.0,21.6,20.6,15.1,22.6,1.9,1.7,0.0066\\n2019-08-13T08:30,12.8,11.5,16.7,12.9,11.9,17.2,1.4,3.1,0.0042\\n \\n CSV Table B: cHPoo7lgKBA,TeH5/klJBIw,MaSbo+Z2DHA,36f4XRtKk+w,I6bLqKSl6OM,09ii68KGAcU,mlTxGdesaBg,ApUalwZOj0I,qVjPndX/zGk\\n0.0,0.0,0.0,2019-06-28T16:08,5.0 out of 5 stars,6040452,No,0.0,2024-04-23T05:00:01.\\n1.7,11.3,17.9,2019-12-04T13:00,5.0 out of 5 stars,6038888,No,11.9,2024-04-23T05:00:01.\\n2.6,6.8,11.9,2020-03-02T07:45,5.0 out of 5 stars,5941356,No,7.1,2024-04-23T05:00:01.\\n-1.0,4.7,8.2,2020-02-16T01:30,5.0 out of 5 stars,6040452,No,5.0,2024-04-23T05:00:01.\\n-0.6,3.2,7.3,2020-01-29T04:00,5.0 out of 5 stars,5941356,No,3.3,2024-04-23T05:00:01.\\n1.7,13.4,16.0,2019-10-27T21:15,4.0 out of 5 stars,5510456,Si,13.7,2024-04-23T05:00:01.\\n-0.2,4.5,8.1,2020-02-21T06:45,5.0 out of 5 stars,6040452,Si,4.5,2024-04-23T05:00:01.\\n2.6,21.5,33.7,2019-11-04T14:45,5.0 out of 5 stars,5510456,Si,21.9,2024-04-23T05:00:01.\\n1.0,4.3,8.9,2019-11-26T06:00,5.0 out of 5 stars,6038888,No,4.6,2024-04-23T05:00:01.\\n1.8,11.3,18.7,2020-02-01T15:30,5.0 out of 5 stars,5026787,No,11.5,2024-04-23T05:00:01.\\n1.4,12.8,15.6,2019-07-23T07:30,5.0 out of 5 stars,6040452,Si,13.1,2024-04-23T05:00:01.\\n2.2,19.6,24.3,2020-03-23T19:45,5.0 out of 5 stars,5510456,No,19.7,2024-04-23T05:00:01.\\n1.3,11.2,19.0,2019-10-29T21:45,5.0 out of 5 stars,6038888,Si,11.5,2024-04-23T05:00:01.\\n1.3,12.2,16.7,2019-12-01T20:45,5.0 out of 5 stars,5941356,Si,12.6,2024-04-23T05:00:01.\\n-0.3,3.2,7.1,2020-01-21T04:15,5.0 out of 5 stars,5510456,No,3.5,2024-04-23T05:00:01.\\n5.9,30.2,38.2,2019-09-26T18:45,5.0 out of 5 stars,5026787,No,30.2,2024-04-23T05:00:01.\\n4.5,11.3,12.4,2020-03-03T09:30,5.0 out of 5 stars,5510456,No,11.8,2024-04-23T05:00:01.\\n0.4,13.2,13.1,2019-08-01T01:30,5.0 out of 5 stars,5026787,No,13.6,2024-04-23T05:00:01.\\n-0.4,7.7,8.3,2020-01-30T07:30,5.0 out of 5 stars,5510456,No,8.1,2024-04-23T05:00:01.\\n0.9,9.7,14.6,2019-10-28T05:00,5.0 out of 5 stars,6038888,No,9.8,2024-04-23T05:00:01.\\n \\n Output: \\n" ]
{"WL2": "TeH5/klJBIw", "VAL2": "ApUalwZOj0I", "VAL1": "MaSbo+Z2DHA", "RVAL1": "cHPoo7lgKBA", "DeviceTimeStamp": "36f4XRtKk+w"}
tablejoin
2024-06-24T00:00:00
d60522bc74ae4e6d7ba1a5e0401e53e4a3d7a7182fed328e72825445ceafba9d
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: URI,Age,2024 Net Worth,Industry,Source of Wealth,Title,Organization,Self-Made,Self-Made Score,Philanthropy Score\\nMarijke Mars,59.0,$9.6B,Food & Beverage,\"Candy, pet food\",,,False,2.0,\\nRay Lee Hunt,81.0,$7.2B,Energy,\"Oil, real estate\",,,False,5.0,2.0\\nArvind Poddar,66.0,$3.2B,Automotive,Tires,,,False,,\\nRoman Abramovich & f,57.0,$9.7B,Diversified,\"Steel, investments\",,,True,,\\nSudhir Mehta,69.0,$5.8B,Healthcare,\"Pharmaceuticals, pow\",,,False,,\\nWang Xing,45.0,$8.8B,Technology,Food delivery,,,True,,\\nTran Ba Duong & fami,64.0,$1.2B,Automotive,Automotive,,,True,,\\nYuri Shefler,56.0,$1.6B,Food & Beverage,Alcohol,,,True,,\\nSeo Jung-jin,66.0,$7.3B,Healthcare,Biotech,,Celltrion Inc.,True,,\\nBenu Gopal Bangur,92.0,$6.8B,Manufacturing,Cement,,,False,,\\nStuart Hoegner,,$2.5B,Finance & Investment,Cryptocurrency,,,True,,\\nGyorgy Gattyan,,$1.1B,Media & Entertainmen,Adult Entertainment,,,True,,\\nKevin David Lehmann,21.0,$3.3B,Fashion & Retail,Drugstores,,,False,,\\nDaniel Kretinsky,48.0,$9.4B,Energy,\"Energy, investments\",,,True,,\\nAndreas Pohl,59.0,$2.4B,Finance & Investment,Mutual funds,,,False,,\\nJared Isaacman,41.0,$1.9B,Technology,Payment processing,,,True,8.0,\\nElisabeth DeLuca & f,76.0,$8.2B,Food & Beverage,Subway,,,False,2.0,2.0\\n \\n CSV Table B: 3dYEUhFn25k,GYfbnsuJx3c,qec7t3TedKU,SmRhS/d2xpk,g4xCeD41TZs,7MoRrR9ITEw,7SxcDOM+98w,j4MgzSCqO6Q\\nNo,0,Weak,6040452,5.0 out of 5 stars,,0,24591000\\nNo,1,Weak,6038888,5.0 out of 5 stars,,0,8334800\\nNo,2,Weak,5941356,5.0 out of 5 stars,,0,9875400\\nNo,3,New,6040452,5.0 out of 5 stars,,0,8338300\\nNo,4,Weak,5941356,5.0 out of 5 stars,Ford Financial Fund,0,8995500\\nSi,5,New,5510456,4.0 out of 5 stars,,0,8564500\\nSi,6,New,6040452,5.0 out of 5 stars,Antofagasta PLC,0,8948500\\nSi,7,New,5510456,5.0 out of 5 stars,,0,11859900\\nNo,8,Weak,6038888,5.0 out of 5 stars,,0,16537400\\nNo,9,New,5026787,5.0 out of 5 stars,,0,11010400\\nSi,10,New,6040452,5.0 out of 5 stars,,0,7534000\\nNo,11,Weak,5510456,5.0 out of 5 stars,,0,9818100\\nSi,12,Weak,6038888,5.0 out of 5 stars,,0,9965000\\nSi,13,Good,5941356,5.0 out of 5 stars,Adani Group,0,20254600\\nNo,14,New,5510456,5.0 out of 5 stars,,0,9989300\\nNo,15,Weak,5026787,5.0 out of 5 stars,,0,12805200\\nNo,16,New,5510456,5.0 out of 5 stars,,0,12652800\\nNo,17,New,5026787,5.0 out of 5 stars,,0,9834300\\n \\n Output: \\n" ]
{"Organization": "7MoRrR9ITEw"}
tablejoin
2024-06-24T00:00:00
e824359153d4fea96a9257ecceb44a3bb95dd0c84f95e2e3964ebdcdf8e8b32b
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: ticker,month,trend,REVS10,REVS20,REVS5,RSTR12,RSTR24,EARNMOM,FiftyTwoWeekHigh\\n600522,2022/6/30,0,1.2333,1.2616,1.1159,0.8618,0.7484,2,1.0\\n423,2018/1/31,0,1.0274,1.0521,0.967,0.1947,0.4284,6,0.6423\\n601877,2021/1/31,0,0.9706,0.9446,0.931,0.3211,0.3986,2,0.798\\n600048,2022/10/31,1,0.8075,0.7801,0.8498,0.0997,-0.0357,2,0.2813\\n300033,2021/10/31,1,0.9708,0.8623,0.9624,-0.2148,0.0836,8,0.3073\\n600029,2019/5/31,1,1.007,0.8479,1.0056,-0.31,-0.1422,2,0.2882\\n601018,2018/9/30,0,1.0049,1.0123,1.0049,-0.3574,-0.1692,4,0.0436\\n600009,2019/12/31,0,0.9994,1.0436,1.0122,0.4317,0.5976,8,0.784\\n60,2018/3/31,1,0.9465,0.9333,1.0319,-0.1841,-0.151,4,0.0677\\n600023,2019/2/28,1,1.0414,1.0717,1.0437,-0.1304,-0.1258,-4,0.3134\\n601211,2019/11/30,1,0.9988,0.9681,1.0109,0.0672,-0.1566,0,0.2955\\n600309,2020/8/31,0,1.0908,1.0842,1.0294,0.5123,0.4557,-6,0.9659\\n2624,2019/11/30,1,1.1367,1.2008,1.0073,0.337,0.0987,2,0.905\\n \\n CSV Table B: NGeDFcnzn7Q,tbWH4NW21KE,urGRA/BeJ1g,ASvdFX/j0/E,80Qm2D0L2Xw,6V+5/UuEIB0,UzDJiMPnvzM,5s14gRQnpFg\\n0.9453,15.6466,0,24591000,6040452,Weak,0.9304,gas\\n1.0154,15.6466,1,8334800,6038888,Weak,0.994,gas\\n1.0249,15.6466,2,9875400,5941356,Weak,0.9896,gas\\n1.0761,15.6466,3,8338300,6040452,New,1.3318,gas\\n0.9926,15.6466,4,8995500,5941356,Weak,1.063,gas\\n1.0123,15.6466,5,8564500,5510456,New,0.9844,gas\\n0.9394,15.6466,6,8948500,6040452,New,0.8686,gas\\n0.9607,15.6466,7,11859900,5510456,New,0.9144,gas\\n1.0,15.6466,8,16537400,6038888,Weak,1.0197,gas\\n0.9579,15.6466,9,11010400,5026787,New,0.9259,gas\\n1.1432,15.6466,10,7534000,6040452,New,1.18,gas\\n0.9908,15.6466,11,9818100,5510456,Weak,0.9134,gas\\n0.9474,15.6466,12,9965000,6038888,Weak,0.9057,gas\\n \\n Output: \\n" ]
{"REVS10": "UzDJiMPnvzM", "REVS5": "NGeDFcnzn7Q"}
tablejoin
2024-06-24T00:00:00
519653e1054c2c48e303e4f8fb1fa2e5fe01d1fd1fb4d26fa45a33b5eb781a3c
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: DeviceTimeStamp,WL1,WL2,WL3,VAL1,VAL2,VAL3,RVAL1,RVAL2,RVAL3\\n2019-07-25T08:01,15.5,10.9,16.3,15.9,11.3,17.3,3.7,2.7,0.0057\\n2020-03-04T15:00,30.3,13.1,25.7,30.7,14.0,28.5,4.6,4.8,0.0122\\n2020-03-24T21:00,15.2,9.7,21.3,15.3,10.1,21.7,2.1,2.7,0.004\\n2019-10-30T04:10,13.8,8.0,15.7,13.8,8.2,16.1,1.0,1.6,0.0034\\n2019-10-30T09:15,16.7,15.8,15.9,17.0,16.1,17.0,3.1,3.1,0.006\\n2020-02-08T06:45,8.3,4.0,9.8,8.3,4.4,10.1,0.5,1.7,0.0025\\n2019-12-08T17:20,14.4,11.9,23.1,14.4,12.4,23.5,0.2,3.3,0.0046\\n2019-08-14T18:00,27.4,33.8,34.8,27.5,33.9,35.4,0.2,3.6,0.0065\\n2019-09-10T19:45,34.0,40.3,39.5,34.2,40.3,39.7,3.9,1.6,0.0033\\n2019-09-13T21:45,20.1,24.4,21.3,20.3,24.5,21.4,3.2,1.8,0.0023\\n2019-11-24T16:45,13.2,11.0,15.5,13.2,11.4,15.9,0.4,3.1,0.0037\\n2020-02-27T16:30,19.3,12.3,22.4,20.0,12.7,22.5,5.3,2.9,0.0021\\n2019-08-28T10:00,14.6,14.3,22.6,14.6,15.1,23.2,0.3,4.8,0.005\\n2019-08-18T02:45,11.0,8.4,14.8,11.0,8.6,15.1,0.0,1.7,0.0027\\n2020-04-10T20:00,20.8,13.2,22.4,20.9,13.3,22.7,2.1,1.4,0.0036\\n2019-08-18T03:55,8.4,8.2,13.5,8.4,8.5,13.6,1.0,1.9,0.002\\n2019-08-18T10:30,15.9,11.1,14.4,16.0,11.3,15.0,1.0,1.8,0.0039\\n2019-08-29T06:45,13.6,9.1,17.3,13.7,9.5,17.7,1.0,2.8,0.0036\\n2019-10-08T04:30,15.4,11.3,25.3,15.7,11.7,25.4,2.8,3.1,0.0008\\n \\n CSV Table B: mlTxGdesaBg,6kQGdj2iXsU,hQKNy+86p+0,2xE2qVXr7UM,J92S/IDpPZA,eshSFvEUsMY,v3NEVV2Owbs\\nNo,1.8,31.1,33.6,33.6,4.4,0\\nNo,1.8,33.2,19.6,19.5,2.7,1\\nNo,2.6,24.5,21.0,20.9,2.7,2\\nNo,1.4,18.0,10.2,10.1,1.4,3\\nNo,0.0,0.0,0.0,0.0,0.0,4\\nSi,1.8,17.9,16.6,16.5,1.6,5\\nSi,1.2,14.6,7.7,7.6,1.2,6\\nSi,0.0,0.0,0.0,0.0,0.0,7\\nNo,2.0,12.5,7.8,7.5,0.9,8\\nNo,1.6,35.5,31.6,31.6,2.0,9\\nSi,2.0,27.2,20.7,20.6,1.4,10\\nNo,3.8,36.4,35.1,34.9,2.0,11\\nSi,1.4,17.5,11.1,11.0,2.0,12\\nSi,3.2,35.0,38.9,38.8,1.4,13\\nNo,4.0,17.6,12.9,12.3,1.5,14\\nNo,3.1,15.7,13.6,13.2,0.0,15\\nNo,4.8,32.1,23.6,23.1,5.6,16\\nNo,1.2,7.5,5.8,5.6,0.7,17\\nNo,2.1,11.2,9.3,9.1,0.0,18\\nNo,2.3,13.0,7.8,7.5,1.8,19\\n \\n Output: \\n" ]
{"RVAL1": "eshSFvEUsMY", "RVAL2": "6kQGdj2iXsU", "WL2": "J92S/IDpPZA", "VAL2": "2xE2qVXr7UM", "VAL1": "hQKNy+86p+0"}
tablejoin
2024-06-24T00:00:00
a783dc9652728632d05f85ac5f944f71ffdfb2cc9dc6ea27e21ad80a96f44e48
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: interaction_id,query_time,domain,question_type,static_or_dynamic,query,answer,alternative_answers,split,page_name\\n144bd3d2-be2b-4fcb-a,\"02/28/2024, 10:04:20\",open,simple_w_condition,static,who is the last empe,toghon temür,[],0,Yuan dynasty - Wikip\\na91df871-089c-4b91-9,\"03/19/2024, 23:17:23\",movie,simple,static,who directed bridget,beeban kidron,[],1,Bridget Jones: The E\\nc4388294-a648-414b-8,\"03/13/2024, 10:07:09\",music,multi-hop,static,who is the american ,lady gaga is the ame,[],1,Grammy Award for Son\\n0b18bc03-a372-4860-a,\"02/28/2024, 07:29:24\",finance,false_premise,fast-changing,on the day that cgi ,invalid question,[],1,Stock info GIB | CGI\\ne04341c6-c7f6-415f-b,\"03/10/2024, 21:43:12\",sports,comparison,static,which team\\'s home ar,chicago bulls,[],1,The Madhouse on Madi\\n07c155bc-34c4-4e8e-a,\"02/28/2024, 07:53:27\",finance,simple,real-time,what\\'s today\\'s curre,i don\\'t know,[],1,DCFC | Tritium DCFC \\n42fa780d-1b01-4dac-a,\"03/15/2024, 15:56:22\",sports,simple_w_condition,slow-changing,who was the leader f,brendan chardonnet,[],0,French Ligue 1 Stats\\n8a687b2a-38db-4132-8,\"03/13/2024, 09:43:37\",music,comparison,slow-changing,who has had more num,drake has had more n,[],0,Hot 100 Songs\\n1c96bf4f-a404-4982-9,\"03/17/2024, 16:46:21\",finance,simple_w_condition,static,what was the low pri,meta low stock price,[],1,\"Meta Platforms, Inc.\"\\n71af3fb4-bb37-4720-b,\"03/13/2024, 09:04:34\",finance,multi-hop,fast-changing,which company in the,the company with the,[],1,D | S&P 500 Stock | \\n655d2141-1090-4aab-8,\"03/05/2024, 23:22:11\",music,aggregation,slow-changing,how many successful ,3,[],1,\"Chris Cornell Songs,\"\\ne6b1f088-a55e-41bd-9,\"03/05/2024, 23:37:26\",movie,post-processing,slow-changing,what was the average,\"$191,671,856\",[],0,\\'Black Panther: Waka\\nb62fdd74-69ec-48e1-9,\"03/15/2024, 16:02:55\",sports,simple_w_condition,static,\"on 2022-10-12, what \",94,[],1,Charlotte Hornets ac\\n \\n CSV Table B: aONjSdwYYDk,PjOW3vib37M,N63uV44/QbQ,31Z18wvwUiM,eJJm7lex974,V9rPaOdeODk,8b3ewM26+SI,AUUii56u8tg\\n[],multi-hop,The 17 Football Club,2024-04-23T05:00:01.,1cba1106-7e25-4777-8,6040452,No,7\\n[],false_premise,Wadishewadi Dam - Wi,2024-04-23T05:00:01.,5c727dee-a307-4c15-a,6038888,No,invalid question\\n[],multi-hop,Drake Albums and Dis,2024-04-23T05:00:01.,21da19e6-56a8-439a-9,5941356,No,drake released his f\\n[],simple_w_condition,Ranking Every NBA De,2024-04-23T05:00:01.,521b6740-ce8d-4cd6-a,6040452,No,tina charles has the\\n[],simple,Trading Volume: Anal,2024-04-23T05:00:01.,76129ef6-369c-481e-a,5941356,No,119\\n[],aggregation,Marilyn Monroe\\'s Hus,2024-04-23T05:00:01.,ff7d4fd0-dccb-4d5c-8,5510456,Si,1\\n[],simple_w_condition,Miami Heat News and ,2024-04-23T05:00:01.,5c5234a3-d684-42ba-8,6040452,Si,denver nuggets\\n[],aggregation,National Football Le,2024-04-23T05:00:01.,639d2cc0-99d6-4346-a,5510456,Si,32\\n[],simple,Pitch Perfect Movie ,2024-04-23T05:00:01.,e2941d28-c26e-4d88-9,6038888,No,9/28/12\\n[],comparison,Bigger career: Adele,2024-04-23T05:00:01.,999a7f32-8a87-4026-b,5026787,No,shakira had more par\\n[],comparison,Sporting Speed Recor,2024-04-23T05:00:01.,d7bcbd24-a0fb-4139-8,6040452,Si,bolt\\n[],aggregation,Super Bowls - Dallas,2024-04-23T05:00:01.,3b9e7284-41a2-43aa-a,5510456,No,the dallas cowboys h\\n[],simple_w_condition,Kelly Gallant | Rott,2024-04-23T05:00:01.,45037240-6762-488e-a,6038888,Si,talons of the eagle\\n[],simple_w_condition,Nike Inc Stock Price,2024-04-23T05:00:01.,8135a393-aedc-4073-a,5941356,Si,$118.55\\n \\n Output: \\n" ]
{"question_type": "PjOW3vib37M", "interaction_id": "eJJm7lex974", "page_name": "N63uV44/QbQ", "answer": "AUUii56u8tg", "alternative_answers": "aONjSdwYYDk"}
tablejoin
2024-06-24T00:00:00
4d351c29bdddf5c41d59cd7bd1b70bb4d2ae2a071ada382d7690066b1cd7764c
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: :@computed_region_dqjc_k29y,:@computed_region_jdnu_jmst,:@computed_region_5d9v_6bui,permitnum,worktype,applicationtype,location,:@computed_region_mfuy_bee2,:@computed_region_2fpw_swv9,:@computed_region_9p4x_9cjt\\n,,,BLD2023-04121,Residential,Building,{'human_address': '{,,,\\n1.0,80.0,26.0,BLD2023-06991,Commercial,Building,{'latitude': '40.771,19.0,18.0,12.0\\n24.0,97.0,26.0,BLD2023-08421,Residential,Building,{'latitude': '40.713,19.0,27.0,573.0\\n12.0,67.0,26.0,BLD2023-05798,Commercial,Building,{'latitude': '40.739,19.0,26.0,358.0\\n1.0,72.0,26.0,BLD2023-07147,Commercial,Building,{'latitude': '40.762,19.0,21.0,495.0\\n23.0,68.0,26.0,BLD2023-03932,Commercial,Building,{'latitude': '40.729,19.0,24.0,243.0\\n12.0,68.0,26.0,BLD2023-06214,Residential,Building,{'latitude': '40.737,19.0,24.0,583.0\\n1.0,72.0,26.0,BLD2023-08511,Commercial,Building,{'latitude': '40.727,19.0,21.0,364.0\\n24.0,68.0,26.0,BLD2023-08557,Residential,Building,{'latitude': '40.744,19.0,24.0,244.0\\n12.0,67.0,26.0,BLD2023-06743,Commercial,Building,{'latitude': '40.734,19.0,26.0,358.0\\n \\n CSV Table B: CMSip4kAsFA,v02+v1698aE,sXpNMhZkCLA,t8DtGa8xUVw,WPAmEDDzzew,SfVC0olx/OE,MOmbowjYQ+I,hOL2mHzD+cg\\nBLD2023-06614,No,26.0,0,358.0,24591000,21.0,Commercial\\nBLD2023-06869,No,26.0,0,361.0,8334800,20.0,Residential\\nBLD2023-05395,No,26.0,0,364.0,9875400,21.0,Residential\\nBLD2023-07713,No,26.0,0,242.0,8338300,21.0,Residential\\nBLD2023-05391,No,26.0,0,364.0,8995500,21.0,Residential\\nBLD2023-02758,Si,26.0,0,474.0,8564500,20.0,Residential\\nBLD2023-06021,Si,26.0,0,357.0,8948500,21.0,Commercial\\nBLD2023-06051,Si,26.0,0,161.0,11859900,20.0,Residential\\nBLD2023-08747,No,26.0,0,14.0,16537400,24.0,Commercial\\nBLD2023-07969,No,26.0,0,573.0,11010400,27.0,Residential\\nBLD2023-05155,Si,26.0,0,567.0,7534000,21.0,Commercial\\n \\n Output: \\n" ]
{":@computed_region_2fpw_swv9": "MOmbowjYQ+I", "worktype": "hOL2mHzD+cg", ":@computed_region_9p4x_9cjt": "WPAmEDDzzew", "permitnum": "CMSip4kAsFA", ":@computed_region_5d9v_6bui": "sXpNMhZkCLA"}
tablejoin
2024-06-24T00:00:00
44953ce33916e7caae16bbce54fbd5a4e00d438924e5e53c0b5c5765ce5a583f
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: tweet_id,airline_sentiment,airline_sentiment_confidence,negativereason,negativereason_confidence,airline,airline_sentiment_gold,name,negativereason_gold,retweet_count\\n567849102731526144,negative,1.0,Customer Service Iss,1.0,US Airways,,TerriHaisten,,0\\n568210087212388353,neutral,1.0,,,Southwest,,livvyports16,,1\\n569824906638073856,negative,1.0,Bad Flight,0.3451,United,,bmalones44,,1\\n569558589628502016,negative,0.6927,Can't Tell,0.6927,United,,4geiger,,0\\n569627744021184513,negative,1.0,Cancelled Flight,0.6673,American,,MatthewJMedlin,,0\\n568809369678315521,negative,1.0,Cancelled Flight,1.0,US Airways,,JeffreyWhitmore,,0\\n569456828511326208,negative,1.0,Late Flight,0.6478,US Airways,,CJLarcheveque,,0\\n569615736387325952,negative,1.0,Bad Flight,0.3487,Southwest,,Ekanewilliams,,0\\n568519360953716736,neutral,1.0,,,Southwest,,MikeWJZ,,1\\n569638848214507520,positive,1.0,,,Delta,,oggito17,,0\\n569275566077165568,neutral,1.0,,,United,,SallyM0nster,,0\\n569826992251473921,neutral,0.6471,,0.0,United,,ohlesliebarker,,0\\n569598614235942912,negative,1.0,Late Flight,1.0,Southwest,,BattleB_studios,,0\\n568460037737324545,neutral,1.0,,,United,,JerseyRic,,0\\n568491905903939584,negative,1.0,Customer Service Iss,0.6579,US Airways,,jekyllandheid12,,0\\n \\n CSV Table B: 3sk7jMfQzck,NYLj0y6YLFA,AG1gKyPX4RQ,QgYMUapyJlU,7dYptJU3eKE,c2A+LJlP174,6lLeTaOQ74g,DAzjs8gwVB0\\nUS Airways,0,5.0 out of 5 stars,0,24591000,,Weak,2024-04-23T05:00:01.\\nAmerican,0,5.0 out of 5 stars,0,8334800,,Weak,2024-04-23T05:00:01.\\nDelta,0,5.0 out of 5 stars,0,9875400,,Weak,2024-04-23T05:00:01.\\nAmerican,0,5.0 out of 5 stars,0,8338300,,New,2024-04-23T05:00:01.\\nUnited,0,5.0 out of 5 stars,0,8995500,,Weak,2024-04-23T05:00:01.\\nAmerican,0,4.0 out of 5 stars,0,8564500,,New,2024-04-23T05:00:01.\\nDelta,0,5.0 out of 5 stars,0,8948500,,New,2024-04-23T05:00:01.\\nUnited,0,5.0 out of 5 stars,0,11859900,,New,2024-04-23T05:00:01.\\nAmerican,0,5.0 out of 5 stars,0,16537400,,Weak,2024-04-23T05:00:01.\\nDelta,0,5.0 out of 5 stars,0,11010400,,New,2024-04-23T05:00:01.\\nUS Airways,0,5.0 out of 5 stars,0,7534000,,New,2024-04-23T05:00:01.\\nSouthwest,0,5.0 out of 5 stars,0,9818100,,Weak,2024-04-23T05:00:01.\\nAmerican,0,5.0 out of 5 stars,0,9965000,,Weak,2024-04-23T05:00:01.\\nUnited,0,5.0 out of 5 stars,0,20254600,,Good,2024-04-23T05:00:01.\\nUnited,0,5.0 out of 5 stars,1,9989300,,New,2024-04-23T05:00:01.\\n \\n Output: \\n" ]
{"airline": "3sk7jMfQzck", "negativereason_gold": "c2A+LJlP174", "retweet_count": "QgYMUapyJlU"}
tablejoin
2024-06-24T00:00:00
a9622ef291b2ff5dac8ee5335d50d52a7bc8bd9fa001130fabaf3ae3d1505100
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: drugName,url,description\\nDexamethasone,https://www.drugs.co,dexamethasone is a c\\nGaramycin,https://www.drugs.co,garamycin is an anti\\nDicyclomine,https://www.drugs.co,dicyclomine relieves\\nOrphenadrine,https://www.drugs.co,orphenadrine is a mu\\nStrattera,https://www.drugs.co,strattera (atomoxeti\\nValsartan,https://www.drugs.co,valsartan is used to\\nSingulair,https://www.drugs.co,singulair (monteluka\\nYupelri,https://www.drugs.co,yupelri (revefenacin\\nKetoconazole,https://www.drugs.co,ketoconazole is an a\\nZolpidem,https://www.drugs.co,zolpidem is a sedati\\nVivitrol,https://www.drugs.co,vivitrol (naltrexone\\nGlimepiride,https://www.drugs.co,glimepiride is an or\\nGlucosamine,https://www.drugs.co,glucosamine is sugar\\nBasaglar,https://www.drugs.co,basaglar (insulin gl\\nAleve,https://www.drugs.co,aleve (naproxen) is \\nStelara,https://www.drugs.co,stelara (ustekinumab\\nYervoy,https://www.drugs.co,yervoy (ipilimumab) \\n \\n CSV Table B: wmYO8hwe094,7SxcDOM+98w\\neffexor xr is a sele,0\\nqdolo is: a strong p,0\\nketotifen is an anti,0\\ntoprol-xl (metoprolo,0\\namlodipine is a calc,0\\nvitamin e is an anti,0\\nprevacid (lansoprazo,0\\nferrous sulfate is a,0\\nbacitracin is an ant,0\\noxybutynin reduces m,0\\njanuvia (sitagliptin,0\\nskelaxin (metaxalone,0\\nwitch hazel is a pla,0\\ntestosterone is a na,0\\nflagyl (metronidazol,0\\nascorbic acid (vitam,0\\n\"niacin, also called \",0\\nprednisolone is a st,0\\n \\n Output: \\n" ]
{"description": "wmYO8hwe094"}
tablejoin
2024-06-24T00:00:00
0bf086ff674cfda54c0293a3ae03a3720d2d1cb755748cc4800d43b375d20a3c
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Age ,Gender,BMI,Fever,Nausea/Vomting,Headache ,Diarrhea ,Fatigue & generalized bone ache ,Jaundice ,Epigastric pain \\n59,2,25,1,1,2,2,2,1,2\\n42,1,28,2,1,2,2,2,1,1\\n61,1,27,2,2,2,2,2,2,1\\n33,2,24,2,1,1,1,2,2,2\\n38,1,29,1,1,2,2,2,1,2\\n49,2,30,2,1,1,1,1,1,2\\n42,1,35,2,1,2,1,2,2,2\\n61,2,23,2,2,1,2,1,2,1\\n34,1,26,1,2,1,2,2,1,2\\n38,1,33,2,2,2,2,2,1,2\\n54,2,30,1,2,2,1,2,2,2\\n \\n CSV Table B: oOd+cX72roM,I4BVsbooFyQ,cslDY8TWfKw,cIESFwIKxuA,F2WS20DtzCs,huCAhXWo21c,YH4pJE8EqH0\\n36,gas,1,Weak,5.0 out of 5 stars,1,6040452\\n53,gas,1,Weak,5.0 out of 5 stars,2,6038888\\n36,gas,2,Weak,5.0 out of 5 stars,2,5941356\\n47,gas,1,New,5.0 out of 5 stars,1,6040452\\n44,gas,2,Weak,5.0 out of 5 stars,1,5941356\\n53,gas,1,New,4.0 out of 5 stars,2,5510456\\n44,gas,1,New,5.0 out of 5 stars,1,6040452\\n37,gas,1,New,5.0 out of 5 stars,2,5510456\\n46,gas,1,Weak,5.0 out of 5 stars,2,6038888\\n61,gas,2,New,5.0 out of 5 stars,2,5026787\\n49,gas,2,New,5.0 out of 5 stars,1,6040452\\n37,gas,2,Weak,5.0 out of 5 stars,2,5510456\\n \\n Output: \\n" ]
{"Fever": "huCAhXWo21c", "Age ": "oOd+cX72roM", "Epigastric pain ": "cslDY8TWfKw"}
tablejoin
2024-06-24T00:00:00
dd7ff515b9cd4c4a6e1d3fe3cb5e14c77123225c73193ce89c104b4f3f80cf22
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: app_no,type,app_date,status,fru_interview_scheduled,drug_test,wav_course,defensive_driving,driver_exam,medical_clearance_form\\n6068038,HDR,2024-02-14T00:00:00.,Approved - License I,Not Applicable,Complete,Complete,Complete,Complete,Complete\\n6070024,HDR,2024-03-11T00:00:00.,Approved - License I,Not Applicable,Complete,Complete,Complete,Complete,Complete\\n6071255,HDR,2024-03-27T00:00:00.,Approved - License I,Not Applicable,Complete,Complete,Complete,Complete,Complete\\n6071006,HDR,2024-03-24T00:00:00.,Incomplete,Not Applicable,Needed,Needed,Needed,Needed,Needed\\n6065967,HDR,2024-01-18T00:00:00.,Incomplete,Not Applicable,Needed,Complete,Complete,Needed,Needed\\n6072382,HDR,2024-04-13T00:00:00.,Incomplete,Not Applicable,Needed,Complete,Complete,Needed,Needed\\n6069398,HDR,2024-03-02T00:00:00.,Incomplete,Not Applicable,Needed,Needed,Needed,Needed,Needed\\n6070427,HDR,2024-03-16T00:00:00.,Incomplete,Not Applicable,Needed,Complete,Needed,Needed,Needed\\n6071162,HDR,2024-03-26T00:00:00.,Approved - License I,Not Applicable,Complete,Complete,Complete,Complete,Complete\\n6067621,HDR,2024-02-08T00:00:00.,Approved - License I,Not Applicable,Complete,Complete,Complete,Complete,Complete\\n6071150,HDR,2024-03-26T00:00:00.,Approved - License I,Not Applicable,Complete,Complete,Complete,Complete,Complete\\n6072162,HDR,2024-04-10T00:00:00.,Incomplete,Not Applicable,Needed,Needed,Needed,Needed,Needed\\n6071242,HDR,2024-03-27T00:00:00.,Incomplete,Not Applicable,Needed,Complete,Needed,Needed,Needed\\n6068081,HDR,2024-02-14T00:00:00.,Approved - License I,Not Applicable,Complete,Complete,Complete,Complete,Complete\\n \\n CSV Table B: kT8cHJ58B7E,LAjKEsrx0pI,qU8fN4BcOE4,4MSYlVBQT9Y,qrA0NE/ugMQ,8QouQFH8JWo,Qiz4gNNSkjU,BkPad8F1Zfw\\nComplete,15.6466,Not Applicable,Complete,5.0 out of 5 stars,0,0,Weak\\nNeeded,15.6466,Not Applicable,Complete,5.0 out of 5 stars,1,0,Weak\\nComplete,15.6466,Not Applicable,Complete,5.0 out of 5 stars,2,0,Weak\\nNeeded,15.6466,Not Applicable,Needed,5.0 out of 5 stars,3,0,New\\nComplete,15.6466,Not Applicable,Complete,5.0 out of 5 stars,4,0,Weak\\nNeeded,15.6466,Not Applicable,Complete,4.0 out of 5 stars,5,0,New\\nNeeded,15.6466,Not Applicable,Complete,5.0 out of 5 stars,6,0,New\\nComplete,15.6466,Not Applicable,Complete,5.0 out of 5 stars,7,0,New\\nComplete,15.6466,Not Applicable,Complete,5.0 out of 5 stars,8,0,Weak\\nNeeded,15.6466,Not Applicable,Needed,5.0 out of 5 stars,9,0,New\\nComplete,15.6466,Not Applicable,Complete,5.0 out of 5 stars,10,0,New\\nComplete,15.6466,Not Applicable,Complete,5.0 out of 5 stars,11,0,Weak\\nNeeded,15.6466,Not Applicable,Complete,5.0 out of 5 stars,12,0,Weak\\nComplete,15.6466,Not Applicable,Complete,5.0 out of 5 stars,13,0,Good\\n \\n Output: \\n" ]
{"defensive_driving": "kT8cHJ58B7E", "fru_interview_scheduled": "qU8fN4BcOE4", "wav_course": "4MSYlVBQT9Y"}
tablejoin
2024-06-24T00:00:00
52b2630e360ae523378662c58b554046d5086033761e830cee61d24e46850889
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: job__,doc__,borough,house__,street_name,block,lot,bin__,job_type,job_status\\n102353819,1,MANHATTAN,200,VESEY STREET,16,140,1000059,A2,R\\n301890522,1,BROOKLYN,3057,BRIGHTON 6 STREET,8676,18,3397165,A2,P\\n421743297,1,QUEENS,35-06,UNION STREET,4961,19,4112190,A3,X\\n301890611,1,BROOKLYN,799,LINCOLN AVENUE,4271,75,3095894,A2,P\\n301812821,1,BROOKLYN,252,HEYWARD STREET,2234,10,3061217,A1,R\\n420181494,1,QUEENS,84-01,37 AVENUE,1458,40,4035835,DM,X\\n301907300,1,BROOKLYN,1224,MYRTLE AVENUE,3216,1,3073099,A2,Q\\n301876469,1,BROOKLYN,1858,61 STREET,5526,29,3132483,A2,X\\n123923861,2,MANHATTAN,122 CANOPY,WEST 145 STREET,2013,44,1060173,DM,E\\n440673718,1,QUEENS,13815,111TH AVENUE,11923,42,4257665,A2,X\\n301927565,1,BROOKLYN,767,MARCY AVENUE,1804,1,3050668,A1,X\\n310061410,1,BROOKLYN,2848,BRIGHTON 7 STREET,7263,44,3392249,A3,X\\n401178569,1,QUEENS,105-50,87 STREET,9149,31,4190407,A2,R\\n301896580,1,BROOKLYN,343,89 STREET,6062,57,3154082,A1,R\\n \\n CSV Table B: Bezp8Kegeiw,pCAjik4u8jI,Qiz4gNNSkjU,qrA0NE/ugMQ,aMV7Uv4npe4,o6kyvs5L8qM,SDXgS2fule4,V9rPaOdeODk\\n24591000,16,0,5.0 out of 5 stars,A2,1000059,MANHATTAN,6040452\\n8334800,6242,0,5.0 out of 5 stars,DM,3161109,BROOKLYN,6038888\\n9875400,1352,0,5.0 out of 5 stars,A2,3324609,BROOKLYN,5941356\\n8338300,15652,0,5.0 out of 5 stars,A2,4299432,QUEENS,6040452\\n8995500,12050,0,5.0 out of 5 stars,A2,4261657,QUEENS,5941356\\n8564500,6802,0,4.0 out of 5 stars,NB,3392757,BROOKLYN,5510456\\n8948500,409,0,5.0 out of 5 stars,A2,1005301,MANHATTAN,6040452\\n11859900,892,0,5.0 out of 5 stars,A2,1078770,MANHATTAN,5510456\\n16537400,1084,0,5.0 out of 5 stars,A3,3414197,BROOKLYN,6038888\\n11010400,6086,0,5.0 out of 5 stars,A2,3154739,BROOKLYN,5026787\\n7534000,2309,0,5.0 out of 5 stars,A1,3061729,BROOKLYN,6040452\\n9818100,13436,0,5.0 out of 5 stars,NB,4286222,QUEENS,5510456\\n9965000,792,0,5.0 out of 5 stars,A2,3013325,BROOKLYN,6038888\\n20254600,4971,0,5.0 out of 5 stars,A3,4112252,QUEENS,5941356\\n \\n Output: \\n" ]
{"block": "pCAjik4u8jI", "bin__": "o6kyvs5L8qM", "job_type": "aMV7Uv4npe4", "borough": "SDXgS2fule4"}
tablejoin
2024-06-24T00:00:00
a215b90180b104679133c979614fe0feeb770b6a3d1df4d41065e15be2ed7051
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: center,center_search_status,facility,occupied,record_date,last_update,country,contact,phone,location\\nKennedy Space Center,Public,Support Areas/1726/H,1957-01-01T00:00:00.,1996-03-01T00:00:00.,2015-06-22T00:00:00.,US,Sheryl Chaffee,321-867-8047,{'latitude': '28.538\\nMichoud Assembly Fac,Public,Port Michoud Facilit,1963-01-01T00:00:00.,2009-01-29T00:00:00.,2013-02-19T00:00:00.,US,Ernest Graham,504.257-2619,{'latitude': '29.950\\nMarshall Space Fligh,Public,ET Acoustic Test Fac,1959-01-01T00:00:00.,1996-03-01T00:00:00.,2014-03-31T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\nGlenn Research Cente,Public,Hypersonic Tunnel Fa,1966-01-01T00:00:00.,1996-03-01T00:00:00.,2015-03-04T00:00:00.,US,Linda C. Elonen-Wrig,216-433-9370,{'latitude': '41.430\\nArmstrong Flight Res,Public,Bldg. 4982 - Aeronau,,2010-04-13T00:00:00.,2014-12-19T00:00:00.,US,Facilities Utilizati,661-276-2585,{'latitude': '35.000\\nLangley Research Cen,Public,Structural Acoustic ,,2012-08-01T00:00:00.,2012-08-02T00:00:00.,US,Sherry Johnson,757.864-3848,{'latitude': '37.086\\nLangley Research Cen,Public,Research Laboratory,1967-01-01T00:00:00.,1996-03-01T00:00:00.,2013-02-25T00:00:00.,US,Sherry Johnson,757.864-3848,{'latitude': '37.086\\nKennedy Space Center,Public,High Bay/M7-360/SSPF,1995-01-01T00:00:00.,1996-03-01T00:00:00.,2015-06-22T00:00:00.,US,Sheryl Chaffee,321-867-8047,{'latitude': '28.538\\nStennis Space Center,Public,Test Facility E-1 #4,1992-01-01T00:00:00.,1996-03-01T00:00:00.,2015-04-06T00:00:00.,US,Robert Bruce,228-688-1646,{'latitude': '30.385\\nMarshall Space Fligh,Public,EP Propulsion Techno,1965-01-01T00:00:00.,1996-03-01T00:00:00.,2014-03-31T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\nAmes Research Center,Public,N237 - HYPERVELOCITY,1964-01-01T00:00:00.,1996-03-01T00:00:00.,2014-06-13T00:00:00.,US,Rocci Caringello,650 603-9506,{'latitude': '37.414\\nAmes Research Center,Public,N204A - SPACE TECHNO,1966-01-01T00:00:00.,1996-03-01T00:00:00.,2014-06-12T00:00:00.,US,Rocci Caringello,650 603-9506,{'latitude': '37.414\\nLangley Research Cen,Public,Materials Processing,1960-01-01T00:00:00.,1996-03-01T00:00:00.,2013-02-19T00:00:00.,US,Sherry Johnson,757.864-3848,{'latitude': '37.086\\nMarshall Space Fligh,Public,EM-20 Automated Ultr,,2006-08-11T00:00:00.,2014-06-02T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\n \\n CSV Table B: NYLj0y6YLFA,YuvUZcQJObM,7dYptJU3eKE,ObftKnUmRWM,DAzjs8gwVB0,mo27EyZRoiE\\n0,Public,24591000,{'latitude': '41.430,2024-04-23T05:00:01.,2015-03-04T00:00:00.\\n0,Public,8334800,{'latitude': '34.178,2024-04-23T05:00:01.,2013-08-07T00:00:00.\\n0,Public,9875400,{'latitude': '34.178,2024-04-23T05:00:01.,2013-08-07T00:00:00.\\n0,Public,8338300,{'latitude': '34.729,2024-04-23T05:00:01.,2014-06-02T00:00:00.\\n0,Public,8995500,{'latitude': '28.538,2024-04-23T05:00:01.,2015-06-22T00:00:00.\\n0,Public,8564500,{'latitude': '37.086,2024-04-23T05:00:01.,2013-02-25T00:00:00.\\n0,Public,8948500,{'latitude': '37.086,2024-04-23T05:00:01.,2013-02-25T00:00:00.\\n0,Public,11859900,{'latitude': '37.086,2024-04-23T05:00:01.,2013-01-28T00:00:00.\\n0,Public,16537400,{'latitude': '29.950,2024-04-23T05:00:01.,2013-02-19T00:00:00.\\n0,Public,11010400,{'latitude': '34.729,2024-04-23T05:00:01.,2014-06-02T00:00:00.\\n0,Public,7534000,{'latitude': '34.178,2024-04-23T05:00:01.,2013-08-07T00:00:00.\\n0,Public,9818100,{'latitude': '38.995,2024-04-23T05:00:01.,2013-08-16T00:00:00.\\n0,Public,9965000,{'latitude': '34.729,2024-04-23T05:00:01.,2014-06-02T00:00:00.\\n0,Public,20254600,{'latitude': '41.430,2024-04-23T05:00:01.,2015-03-04T00:00:00.\\n0,Public,9989300,{'latitude': '34.729,2024-04-23T05:00:01.,2014-06-02T00:00:00.\\n \\n Output: \\n" ]
{"location": "ObftKnUmRWM", "center_search_status": "YuvUZcQJObM", "last_update": "mo27EyZRoiE"}
tablejoin
2024-06-24T00:00:00
d03bcee55bda5e582cc13547ab9bf898fbd1324fd5690481cc0d8a4ae9fd24f9
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: tweet_id,airline_sentiment,airline_sentiment_confidence,negativereason,negativereason_confidence,airline,airline_sentiment_gold,name,negativereason_gold,retweet_count\\n569518979103924224,neutral,0.64,,0.0,United,,throthra,,0\\n569407352299847680,negative,0.7029,Late Flight,0.3619,United,,MarkGilden,,0\\n570177012360462336,negative,1.0,longlines,0.3611,American,,JayFranceschi,,0\\n568808318560550912,positive,0.6838,,,Delta,,matthewhirsch,,0\\n569490427625086976,negative,1.0,Late Flight,1.0,Delta,,TIURach2014,,0\\n569925291331735552,negative,1.0,Customer Service Iss,1.0,American,,JustineTomkins,,0\\n568148213418455041,positive,1.0,,,United,,IrisSanchezCDE,,0\\n568172386903851008,positive,1.0,,,Delta,,MarissaBreton,,0\\n569342508553121795,negative,1.0,Customer Service Iss,1.0,US Airways,,realmattberry,,0\\n569667638651170816,neutral,1.0,,,Southwest,,OneToughShark,,0\\n568272244792631296,negative,1.0,Late Flight,1.0,United,,Atrain_8,,1\\n569661113593425920,negative,1.0,Bad Flight,0.3481,US Airways,,ElmiraBudMan,,0\\n569941957490774016,positive,1.0,,,Virgin America,,TaylorLumsden,,0\\n570296616688750592,negative,0.6725,Flight Booking Probl,0.6725,American,,AesaGaming,,0\\n569826992251473921,neutral,0.6471,,0.0,United,,ohlesliebarker,,0\\n \\n CSV Table B: a6oKqAbhiYE,C8eRZt40qKM,c2A+LJlP174,jUs0oGda1Ms,3nNNqrYxl08,q76k2bUnOlk,NYLj0y6YLFA\\ngas,American,,Can't Tell,0.6753,569895817403768833,0\\ngas,American,,Cancelled Flight,1.0,569870252508635136,0\\ngas,US Airways,,,0.6682,569638479157723136,0\\ngas,United,,Customer Service Iss,1.0,569722020776116224,0\\ngas,Delta,,Late Flight,0.682,569535236884664320,0\\ngas,US Airways,,Cancelled Flight,1.0,569698944084680704,0\\ngas,Southwest,,,1.0,568981498046623744,0\\ngas,United,,Flight Booking Probl,1.0,568840701850419200,0\\ngas,United,,Customer Service Iss,1.0,567789435795861504,0\\ngas,United,,Customer Service Iss,1.0,568574014505029632,0\\ngas,Southwest,,Customer Service Iss,1.0,569334621252526080,0\\ngas,Southwest,,,1.0,570041591714455552,0\\ngas,American,,,0.6677,570033000777457664,0\\ngas,Virgin America,,,1.0,570010571707256832,0\\ngas,Delta,,,1.0,568910753652199424,0\\n \\n Output: \\n" ]
{"negativereason_gold": "c2A+LJlP174", "airline": "C8eRZt40qKM", "airline_sentiment_confidence": "3nNNqrYxl08", "tweet_id": "q76k2bUnOlk", "negativereason": "jUs0oGda1Ms", "retweet_count": "NYLj0y6YLFA"}
tablejoin
2024-06-24T00:00:00
b8a3e0f6c177bbef546e0dd490a0193b02124e193d5ffe093d86963449cba596
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Age ,Gender,BMI,Fever,Nausea/Vomting,Headache ,Diarrhea ,Fatigue & generalized bone ache ,Jaundice ,Epigastric pain \\n39,2,33,2,1,2,1,1,1,2\\n48,1,24,1,1,1,2,2,2,2\\n52,1,28,2,2,1,2,1,2,2\\n58,1,31,2,2,2,1,1,1,1\\n49,1,33,2,2,1,1,2,1,1\\n58,2,23,1,1,2,2,1,2,2\\n53,2,31,1,1,1,1,2,2,2\\n35,2,25,2,2,1,2,2,2,1\\n54,2,34,1,2,1,1,2,2,2\\n38,1,27,1,2,2,1,1,2,2\\n56,1,26,1,2,1,1,1,2,1\\n \\n CSV Table B: F2WS20DtzCs,ODDCZ5voqXs,YH4pJE8EqH0,kbyPjM4nFp0,cIESFwIKxuA,o1aE2g76cKc,w8B7SY5DO6Y\\n5.0 out of 5 stars,15.6466,6040452,2024-04-23T05:00:01.,Weak,1,No\\n5.0 out of 5 stars,15.6466,6038888,2024-04-23T05:00:01.,Weak,2,No\\n5.0 out of 5 stars,15.6466,5941356,2024-04-23T05:00:01.,Weak,1,No\\n5.0 out of 5 stars,15.6466,6040452,2024-04-23T05:00:01.,New,1,No\\n5.0 out of 5 stars,15.6466,5941356,2024-04-23T05:00:01.,Weak,2,No\\n4.0 out of 5 stars,15.6466,5510456,2024-04-23T05:00:01.,New,2,Si\\n5.0 out of 5 stars,15.6466,6040452,2024-04-23T05:00:01.,New,2,Si\\n5.0 out of 5 stars,15.6466,5510456,2024-04-23T05:00:01.,New,1,Si\\n5.0 out of 5 stars,15.6466,6038888,2024-04-23T05:00:01.,Weak,1,No\\n5.0 out of 5 stars,15.6466,5026787,2024-04-23T05:00:01.,New,2,No\\n5.0 out of 5 stars,15.6466,6040452,2024-04-23T05:00:01.,New,1,Si\\n5.0 out of 5 stars,15.6466,5510456,2024-04-23T05:00:01.,Weak,2,No\\n \\n Output: \\n" ]
{"Headache ": "o1aE2g76cKc"}
tablejoin
2024-06-24T00:00:00
2f1500d37ffd0e42cd2c89c04011cbbf5dd6b1f71f495156b016a967270cdded
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: REC_ID,Species,Continent.of.Origin,Country.of.Origin,Harvest.Year,Expiration,Variety,Color,Processing.Method,Aroma\\n1285,Arabica,North America,Mexico,2013.0,03/29/14,Typica,Green,Washed / Wet,7.08\\n454,Arabica,Africa,Tanzania,2014.0,12/12/15,Other,Bluish-Green,Washed / Wet,7.58\\n913,Arabica,North America,Guatemala,2017.0,06/01/18,Bourbon,Green,,7.5\\n864,Arabica,North America,Mexico,2012.0,09/10/13,Mundo Novo,Green,Washed / Wet,7.42\\n596,Arabica,North America,United States,2013.0,02/05/15,Hawaiian Kona,Blue-Green,Natural / Dry,7.67\\n1138,Arabica,North America,United States,,09/21/12,,,,7.5\\n985,Arabica,North America,United States,,09/21/12,,,,7.25\\n1260,Arabica,Asia,India,2016.0,01/16/18,,Green,Natural / Dry,7.67\\n820,Arabica,North America,Guatemala,2015.0,04/19/16,Catuai,Green,Washed / Wet,7.58\\n1294,Arabica,North America,Mexico,2014.0,05/08/15,Typica,,Washed / Wet,7.08\\n246,Arabica,North America,Guatemala,2014.0,06/27/15,Bourbon,Green,Other,7.75\\n1193,Arabica,North America,United States,2013.0,06/09/15,Other,Green,Washed / Wet,7.42\\n916,Arabica,North America,Costa Rica,2014.0,01/07/16,Caturra,Green,Washed / Wet,7.83\\n1076,Arabica,North America,United States,2013.0,02/04/15,Hawaiian Kona,Green,Natural / Dry,7.42\\n735,Arabica,Asia,Taiwan,2016.0,02/13/18,,Blue-Green,,7.0\\n328,Arabica,South America,Colombia,2012.0,11/22/13,Caturra,Green,Washed / Wet,7.75\\n312,Arabica,South America,Colombia,2010.0,02/09/12,,,,7.75\\n625,Arabica,Asia,Thailand,2012.0,06/13/13,Other,Bluish-Green,Washed / Wet,7.83\\n1333,Robusta,North America,United States,2012.0,02/28/13,Arusha,Green,Natural / Dry,7.92\\n \\n CSV Table B: x0YTt9hPYFI,vU50Gku+N1g,fg/VVHUVHIQ,zfzQ4Z9Dt5o,9lfBveG7CWM,6oyt+mdSeHI,iJKOBRCgJI0,LOldZF4dJII\\n2012.0,Bluish-Green,806,Typica,Weak,7.42,Washed / Wet,Asia\\n2014.0,,641,Other,Weak,7.75,Washed / Wet,Africa\\n2013.0,Green,406,Catuai,Weak,7.5,Washed / Wet,North America\\n2010.0,,1167,,New,7.25,,South America\\n2009.0,,531,Caturra,Weak,7.58,,North America\\n2013.0,Bluish-Green,1267,,New,7.5,Natural / Dry,North America\\n2012.0,Bluish-Green,430,Hawaiian Kona,New,7.58,Natural / Dry,North America\\n2012.0,Green,155,Caturra,New,7.42,Washed / Wet,South America\\n2012.0,Green,1126,,Weak,7.33,Washed / Wet,Asia\\n2014.0,,989,Pache Comun,New,7.42,Natural / Dry,North America\\n2012.0,Green,1203,Typica,New,7.17,Washed / Wet,North America\\n2012.0,,1153,Bourbon,Weak,7.25,Washed / Wet,North America\\n2014.0,,455,Caturra,Weak,7.58,Washed / Wet,South America\\n2012.0,Green,1058,Bourbon,Good,7.0,Washed / Wet,North America\\n2011.0,Green,32,Bourbon,New,8.5,Natural / Dry,South America\\n2016.0,Bluish-Green,1158,Bourbon,Weak,7.25,Washed / Wet,North America\\n2014.0,,10,,New,8.17,Natural / Dry,Africa\\n2012.0,Green,1258,Other,New,7.08,Washed / Wet,North America\\n2012.0,,1268,Typica,New,7.42,Washed / Wet,North America\\n \\n Output: \\n" ]
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"}
tablejoin
2024-06-24T00:00:00
b2c9accaab7ee5cac67f482c19dcda8942fb409b25b604ef1136367f56d07fd0
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: drugName,url,description\\nSimvastatin,https://www.drugs.co,simvastatin belongs \\nOxandrolone,https://www.drugs.co,oxandrolone is a man\\nEnbrel,https://www.drugs.co,enbrel (etanercept) \\nGeodon,https://www.drugs.co,geodon (ziprasidone)\\nBotox,https://www.drugs.co,botox (onabotulinumt\\nDigoxin,https://www.drugs.co,digoxin is derived f\\nFlexeril,https://www.drugs.co,flexeril (cyclobenza\\nMethadone,https://www.drugs.co,methadone is an opio\\nLosartan,https://www.drugs.co,losartan (cozaar) be\\nHyoscyamine,https://www.drugs.co,hyoscyamine is used \\nQbrelis,https://www.drugs.co,qbrelis is an ace in\\nKeflex,https://www.drugs.co,keflex (cephalexin) \\nTemazepam,https://www.drugs.co,temazepam is a benzo\\nVicodin,https://www.drugs.co,vicodin contains a c\\nMorphine,https://www.drugs.co,morphine is an opioi\\nNystatin and triamci,https://www.drugs.co,nystatin is an antif\\nMethotrexate,https://www.drugs.co,methotrexate interfe\\n \\n CSV Table B: 7SxcDOM+98w,d6QN21UPOVs,ChUIBl78HP8\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n0,https://www.drugs.co,gas\\n \\n Output: \\n" ]
{"url": "d6QN21UPOVs"}
tablejoin
2024-06-24T00:00:00
9318064da8b360eff10f17cdbde9ee624a2112203d8239516e536a0e5bec44e9
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Country,Inequality HDI\\nNauru,2\\nKuwait,1\\nCongo (Democratic Re,3\\nLiechtenstein,0\\nCzechia,0\\nEl Salvador,3\\nParaguay,2\\nNicaragua,3\\nBelize,2\\nBelgium,0\\nSouth Sudan,3\\nBotswana,3\\nAngola,3\\nUnited Arab Emirates,0\\n \\n CSV Table B: L3foh6+TuqY,NYLj0y6YLFA\\nCyprus,0\\nUkraine,0\\nEcuador,0\\nBrazil,0\\nLibya,0\\nLiberia,0\\nBolivia (Plurination,0\\nKiribati,0\\nGuatemala,0\\nBahamas,0\\nLebanon,0\\nIndia,0\\nYemen,0\\nBarbados,0\\nBurundi,0\\n \\n Output: \\n" ]
{"Country": "L3foh6+TuqY"}
tablejoin
2024-06-24T00:00:00
04ba0a2b8fe86cdd255723961356723f6de221cbe6bbc7af4b9ac93d45cd40ec
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: longitude,latitude,start_date,end_date,source,horizon_lower,horizon_upper,aluminium_extractable,boron_extractable,calcium_extractable\\n35.50963,-13.41183,01/01/2008,31/12/2018,afsis_spectral,20,0,920.734,,1042.361\\n34.22425,-11.65423,01/01/2008,31/12/2018,afsis_spectral,20,0,1339.417,,2882.606\\n31.81264,-8.63489,01/01/2008,31/12/2018,afsis_spectral,20,0,668.024,,360.559\\n36.487,-6.07697,01/01/2008,31/12/2018,afsis_spectral,20,0,677.402,,811.649\\n35.46519,-7.72076,01/01/2008,31/12/2018,afsis_spectral,50,20,506.082,,395.229\\n34.26721,-4.26873,01/01/2008,31/12/2018,afsis_spectral,50,20,849.618,,1295.836\\n32.34213,-3.17727,01/01/2008,31/12/2018,afsis_spectral,50,20,844.028,,999.168\\n31.06515,-6.21487,01/01/2008,31/12/2018,afsis_spectral,50,20,500.886,,292.74\\n36.00592,-7.66049,01/01/2008,31/12/2018,afsis_spectral,50,20,795.988,,452.385\\n-2.38906,7.39374,01/01/2008,31/12/2018,afsis_spectral,50,20,523.359,,2391.241\\n \\n CSV Table B: MkLAdzp+esw,+I7cBfMYFoQ,SeflMNbyB9c,6oYoa6ynUjM,+ppuhrWxZm0,UHgQMYIJ9TU,GlQankwBpC4,lGwUkVW6H7g\\nafsis_spectral,15.6466,Weak,708.277,0,,0,20\\nafsis_spectral,15.6466,Weak,682.892,1,,0,20\\nafsis_spectral,15.6466,Weak,1036.355,2,,20,50\\nafsis_spectral,15.6466,New,1264.034,3,,20,50\\nafsis_spectral,15.6466,Weak,597.63,4,,20,50\\nafsis_spectral,15.6466,New,772.719,5,,20,50\\nafsis_spectral,15.6466,New,588.3375,6,,0,20\\nafsis_spectral,15.6466,New,913.833,7,,20,50\\nafsis_spectral,15.6466,Weak,778.952,8,,20,50\\nafsis_spectral,15.6466,New,581.775,9,,20,50\\nafsis_spectral,15.6466,New,518.874,10,,0,20\\n \\n Output: \\n" ]
{"horizon_upper": "GlQankwBpC4", "horizon_lower": "lGwUkVW6H7g", "aluminium_extractable": "6oYoa6ynUjM", "boron_extractable": "UHgQMYIJ9TU", "source": "MkLAdzp+esw"}
tablejoin
2024-06-24T00:00:00
145cfcc10c148be13cc52c96a77611ff6fa5a2b2f756b7f8f9bc0220404a83d7
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: id,dept_name,program_name,org_number,measure_name,measure_id,active,priority_measure,budget_book,fiscal_year\\n35,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2017-18\\n1,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2011-12\\n41,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2019-20\\n21,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2015-16\\n3,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2013-14\\n4,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2014-15\\n4,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2014-15\\n4,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2014-15\\n3,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2013-14\\n40,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2018-19\\n \\n CSV Table B: SHtiPaG4vSU,bG37FIQSUl4,qQ/ysRVsisg,53NiJOr4DrA,NxnXOP1axWA,0dfsuiTLoSQ,sLO/8JuHP+A,Gu1a6Jx2RSE\\n15.6466,gas,5.0 out of 5 stars,YES,6040452,4510B,Weak,0\\n15.6466,gas,5.0 out of 5 stars,YES,6038888,4510B,Weak,1\\n15.6466,gas,5.0 out of 5 stars,YES,5941356,4510B,Weak,2\\n15.6466,gas,5.0 out of 5 stars,YES,6040452,4510B,New,3\\n15.6466,gas,5.0 out of 5 stars,YES,5941356,4510B,Weak,4\\n15.6466,gas,4.0 out of 5 stars,YES,5510456,4510B,New,5\\n15.6466,gas,5.0 out of 5 stars,YES,6040452,4510B,New,6\\n15.6466,gas,5.0 out of 5 stars,YES,5510456,4510B,New,7\\n15.6466,gas,5.0 out of 5 stars,YES,6038888,4510B,Weak,8\\n15.6466,gas,5.0 out of 5 stars,YES,5026787,4510B,New,9\\n \\n Output: \\n" ]
{"org_number": "0dfsuiTLoSQ", "priority_measure": "53NiJOr4DrA"}
tablejoin
2024-06-24T00:00:00
1555bac3606cf98dc257767598c8a85738893f74b07a0a7f2d150751d0ab4939
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: zipcode,year,life_expectancy\\n94965,2000,78.37\\n94103,2000,72.79\\n94560,2013,82.51\\n94519,2000,77.55\\n94514,2013,84.76\\n95694,2013,80.28\\n94550,2013,81.33\\n94014,2013,81.85\\n95419,2000,79.57\\n94920,2000,83.01\\n94972,2000,79.81\\n94602,2000,78.07\\n95465,2013,82.92\\n94803,2000,77.16\\n94542,2000,77.27\\n94924,2000,79.37\\n94598,2013,84.46\\n94596,2000,81.06\\n94526,2013,84.11\\n \\n CSV Table B: j0ihiCMCXaU,5P5CL2d6lvo\\n0,2013\\n0,2000\\n0,2000\\n0,2000\\n0,2000\\n0,2013\\n0,2000\\n0,2013\\n0,2013\\n0,2013\\n0,2000\\n0,2000\\n0,2013\\n0,2000\\n0,2000\\n0,2000\\n0,2000\\n0,2000\\n0,2000\\n0,2000\\n \\n Output: \\n" ]
{"year": "5P5CL2d6lvo"}
tablejoin
2024-06-24T00:00:00
fd0046f3c752ad7a6ce735aff42247b449563c3c664852793c698369c0046c93
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: zipcode,year,life_expectancy\\n94531,2013,79.02\\n94539,2013,85.45\\n94533,2013,79.4\\n94518,2000,79.18\\n95132,2013,82.45\\n95430,2000,79.81\\n94924,2000,79.37\\n94549,2000,80.92\\n95461,2000,81.04\\n94577,2013,81.02\\n94305,2000,81.45\\n94535,2013,79.4\\n94930,2013,85.98\\n94619,2000,78.3\\n94063,2000,78.4\\n95070,2000,81.04\\n95401,2013,79.95\\n94074,2000,80.36\\n94609,2013,78.0\\n \\n CSV Table B: j0ihiCMCXaU,gG+PnzOD1mw,DOgXTTuHGbo\\n0,94583,2000\\n0,94506,2013\\n0,95446,2000\\n0,94567,2013\\n0,95120,2000\\n0,94306,2000\\n0,95687,2000\\n0,94040,2013\\n0,94567,2000\\n0,95688,2013\\n0,94938,2013\\n0,95037,2000\\n0,94702,2013\\n0,95121,2000\\n0,95037,2013\\n0,94607,2013\\n0,94929,2000\\n0,94705,2013\\n0,94608,2000\\n0,94109,2013\\n \\n Output: \\n" ]
{"year": "DOgXTTuHGbo", "zipcode": "gG+PnzOD1mw"}
tablejoin
2024-06-24T00:00:00
31b308131501939d06a5af26b6e26500ab71fc1585a16324abda514a2276ed14
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Unnamed: 0,carat,cut,color,clarity,depth,table,price,x,y\\n32692,0.31,Premium,G,VS1,62.8,58.0,802,4.3,4.27\\n23608,1.56,Ideal,H,VS2,61.5,56.0,11636,7.5,7.46\\n590,0.82,Very Good,H,SI1,60.7,56.0,2836,6.04,6.06\\n35579,0.35,Ideal,F,VS2,62.4,55.0,906,4.53,4.51\\n4129,1.52,Premium,I,I1,61.2,58.0,3541,7.43,7.35\\n19543,1.59,Ideal,J,SI1,62.4,55.0,8176,7.45,7.48\\n1140,0.65,Ideal,F,VVS2,61.3,56.0,2921,5.58,5.61\\n50452,0.7,Ideal,F,SI1,59.9,57.0,2264,5.74,5.82\\n18989,1.34,Premium,H,VS2,62.3,60.0,7816,7.05,7.02\\n38141,0.3,Ideal,G,VVS1,62.6,54.0,1013,4.28,4.25\\n17329,1.01,Ideal,G,VS1,62.7,56.0,6951,6.4,6.35\\n28904,0.3,Good,H,VVS1,63.3,55.0,684,4.29,4.34\\n44114,0.46,Ideal,G,IF,61.6,54.0,1558,4.97,5.0\\n40890,0.56,Fair,F,SI1,61.6,61.0,1176,5.38,5.21\\n51423,0.57,Ideal,E,VVS2,62.5,54.0,2372,5.35,5.28\\n53649,0.71,Ideal,E,SI1,61.3,57.0,2704,5.81,5.78\\n44809,0.5,Ideal,E,VS2,60.0,57.0,1624,5.12,5.15\\n28132,0.29,Very Good,D,VVS2,62.9,58.0,664,4.2,4.29\\n \\n CSV Table B: ChUIBl78HP8,SmRhS/d2xpk,v8hZSaJ4hmU,flTrJL0jwco,AHrHgGEpT+w,g4xCeD41TZs,DyGrEveH2Yg,Rjl6n9rquo8,aJYFJF6+PfY,j4MgzSCqO6Q\\ngas,6040452,D,Premium,2387,5.0 out of 5 stars,5.14,51555,2024-04-23T05:00:01.,24591000\\ngas,6038888,D,Ideal,1763,5.0 out of 5 stars,5.27,46383,2024-04-23T05:00:01.,8334800\\ngas,5941356,E,Fair,3508,5.0 out of 5 stars,6.03,3971,2024-04-23T05:00:01.,9875400\\ngas,6040452,F,Premium,7632,5.0 out of 5 stars,6.56,18669,2024-04-23T05:00:01.,8338300\\ngas,5941356,H,Ideal,17141,5.0 out of 5 stars,8.03,27014,2024-04-23T05:00:01.,8995500\\ngas,5510456,I,Ideal,4511,4.0 out of 5 stars,6.36,8998,2024-04-23T05:00:01.,8564500\\ngas,6040452,G,Good,4678,5.0 out of 5 stars,6.51,9860,2024-04-23T05:00:01.,8948500\\ngas,5510456,J,Good,3149,5.0 out of 5 stars,6.33,2249,2024-04-23T05:00:01.,11859900\\ngas,6038888,F,Very Good,5078,5.0 out of 5 stars,6.4,11755,2024-04-23T05:00:01.,16537400\\ngas,5026787,F,Ideal,673,5.0 out of 5 stars,4.32,28497,2024-04-23T05:00:01.,11010400\\ngas,6040452,G,Ideal,9465,5.0 out of 5 stars,6.54,21310,2024-04-23T05:00:01.,7534000\\ngas,5510456,E,Very Good,5113,5.0 out of 5 stars,6.32,11887,2024-04-23T05:00:01.,9818100\\ngas,6038888,G,Very Good,15241,5.0 out of 5 stars,7.86,26042,2024-04-23T05:00:01.,9965000\\ngas,5941356,G,Ideal,1868,5.0 out of 5 stars,5.34,47524,2024-04-23T05:00:01.,20254600\\ngas,5510456,D,Premium,11760,5.0 out of 5 stars,7.23,23696,2024-04-23T05:00:01.,9989300\\ngas,5026787,F,Premium,17746,5.0 out of 5 stars,7.96,27281,2024-04-23T05:00:01.,12805200\\ngas,5510456,G,Very Good,4922,5.0 out of 5 stars,6.2,11075,2024-04-23T05:00:01.,12652800\\ngas,5026787,D,Very Good,4466,5.0 out of 5 stars,6.17,8758,2024-04-23T05:00:01.,9834300\\n \\n Output: \\n" ]
{"price": "AHrHgGEpT+w", "color": "v8hZSaJ4hmU", "Unnamed: 0": "Rjl6n9rquo8", "cut": "flTrJL0jwco", "y": "DyGrEveH2Yg"}
tablejoin
2024-06-24T00:00:00
27da7f0ed5df368fa2d311fe3be17bbece8769109b41fc6e7768706d5d26f662
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: basisid,data_category,data_subcategory,data_set,description,data_steward,primary_uses,format,unit_of_analysis,principal_use\\n7dc60380-2dea-449a-a,Policy,Land Use,Farmland Mapping and,\"Established in 1982,\",Michael Smith,UrbanSim Modeling; P,geo,,TBD\\n849c4c98-4731-45bd-b,Environment,Natural Hazards,Fire Severity Risk: ,Features represent M,Michael Germeraad,Resiliance Programs;,geo,,TBD\\nd2f53550-37ec-4d98-9,Environment,Physical,Ultramafic Rock (200,Ultramafic rock depo,Michael Smith,Resiliance Programs;,geo,,Plan Bay Area 2040 E\\ndb70b910-7741-11e9-8,Environment,Natural Hazards,Alquist-Priolo Earth,This feature set con,Michael Germeraad,Resiliance Programs;,geo,parcel,TBD\\ndb70c7ca-7741-11e9-8,Environment,Natural Hazards,Liquefaction Suscept,This data set repres,Michael Germeraad,Resiliance Programs;,geo,parcel,TBD\\ndb70b17c-7741-11e9-8,Environment,Natural Hazards,Landslide Study Zone,Earthquake induced l,Michael Germeraad,Resiliance Programs;,geo,parcel,TBD\\ndb70c1d0-7741-11e9-8,Environment,Natural Hazards,Federal Emergency Ma,Federal Emergency Ma,Michael Germeraad,Resiliance Programs;,geo,parcel,TBD\\ndb70cdce-7741-11e9-8,Environment,Natural Hazards,Sea Level Rise (0 to,Locations along shor,Michael Germeraad,Resiliance Programs;,geo,parcel,TBD\\ndb70a3da-7741-11e9-8,Policy,Land Use,General Plan Land Us,Land Use Policies de,Michael Reilly,\"UrbanSim Modeling, R\",geo,parcel,TBD\\ndb70af1a-7741-11e9-8,Policy,Regional Policies,Transit Priority Are,Areas that are withi,Dave Vautin,UrbanSim Modeling; R,geo,sub city areas,TBD\\ndb70bca8-7741-11e9-8,Policy,Land Use,Non-Developable Site,Sites designated by ,Michael Reilly,UrbanSim Modeling,\"table, geo\",parcel,TBD\\n \\n CSV Table B: YH4pJE8EqH0,6D6C5OoLPL0,3h5pywnGh5w,7rZUjQZBAfU,g2kuxlmrx7M,EDrdgfL7sCc,UtepfhoKJl0\\n6040452,UrbanSim Modeling,db70b7da-7741-11e9-8,table,parcel,Development Policies,Michael Reilly\\n6038888,Housing Program; Res,db709656-7741-11e9-8,table,parcel,Housing Preservation,Gillian Adams\\n5941356,Resiliance Programs;,6b68ee2c-53d4-4b00-8,geo,,Fire Severity Risk: ,Michael Germeraad\\n6040452,Resiliance Programs;,c6ba8375-8a35-4ded-9,geo,,NOAA 2ft Sea Level R,Michael Germeraad\\n5941356,\"UrbanSim Modeling, R\",db70b67c-7741-11e9-8,geo,jurisdiction,Urban Growth Boundar,Michael Reilly\\n5510456,Housing Program; Res,db70a8a8-7741-11e9-8,geo,parcel,Bay Area Housing Opp,Gillian Adams\\n6040452,Resiliance Programs;,df8deccc-87cf-4796-8,geo,,NOAA 2ft Sea Level R,Michael Germeraad\\n5510456,Resiliance Programs;,db70ba46-7741-11e9-8,geo,parcel,Historic Wildfire Pe,Michael Germeraad\\n6038888,Resiliance Programs;,db70cb44-7741-11e9-8,geo,parcel,Wildfire Threat,Michael Germeraad\\n5026787,Resiliance Programs;,db70926e-7741-11e9-8,table,parcel,Local Hazard Resilie,Michael Germeraad\\n6040452,Resiliance Programs;,db70c43c-7741-11e9-8,geo,parcel,Probabilistic Seismi,Michael Germeraad\\n5510456,Resiliance Programs;,27920239-c9fd-4a31-a,geo,,Adapting to Rising T,Michael Smith\\n \\n Output: \\n" ]
{"data_set": "EDrdgfL7sCc", "data_steward": "UtepfhoKJl0", "unit_of_analysis": "g2kuxlmrx7M", "primary_uses": "6D6C5OoLPL0", "format": "7rZUjQZBAfU", "basisid": "3h5pywnGh5w"}
tablejoin
2024-06-24T00:00:00
eeec6c1afcb16c44895a770343d4c21c6eb88d2902ac8dc1568a6940d9502610
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: time,power,temp,humidity,light,CO2,dust\\n2015-08-06 13:35:30,0.572,34,34,23,1329,6.49\\n2015-08-05 08:34:28,0.0,31,40,8,1184,14.42\\n2015-08-30 12:00:30,-1.0,34,29,20,2000,9.52\\n2015-08-14 05:36:37,0.0,34,33,0,2000,12.63\\n2015-08-17 14:26:16,0.0,35,29,11,2000,9.94\\n2015-08-11 01:17:52,0.0,33,34,0,2000,25.68\\n2015-08-01 01:48:22,0.0,32,41,0,973,25.11\\n2015-08-29 18:59:33,-1.0,35,28,23,2000,5.32\\n2015-08-09 11:57:26,0.528,32,35,7,1806,10.68\\n2015-08-06 06:26:53,0.0,31,38,0,1300,12.87\\n2015-08-17 21:01:45,0.0,35,30,26,2000,5.08\\n2015-08-06 11:37:33,0.0,34,36,22,1374,14.07\\n2015-08-01 23:56:50,0.0,33,40,0,956,20.39\\n2015-08-04 10:11:26,0.0,32,39,19,1102,10.26\\n2015-08-10 08:12:01,-1.0,33,34,18,2000,15.09\\n2015-08-10 12:07:54,0.088,33,33,14,2000,8.53\\n \\n CSV Table B: +TcFRhetc3o,0bFLf6WxD8A,Y70Tlv14K3Y,5ArEgCtuDyM,9etcI5xa42c\\n6040452,15.6466,-1.0,24591000,2024-04-23T05:00:01.\\n6038888,15.6466,0.0,8334800,2024-04-23T05:00:01.\\n5941356,15.6466,0.0,9875400,2024-04-23T05:00:01.\\n6040452,15.6466,-1.0,8338300,2024-04-23T05:00:01.\\n5941356,15.6466,-1.0,8995500,2024-04-23T05:00:01.\\n5510456,15.6466,-1.0,8564500,2024-04-23T05:00:01.\\n6040452,15.6466,0.0,8948500,2024-04-23T05:00:01.\\n5510456,15.6466,0.0,11859900,2024-04-23T05:00:01.\\n6038888,15.6466,0.11,16537400,2024-04-23T05:00:01.\\n5026787,15.6466,0.0,11010400,2024-04-23T05:00:01.\\n6040452,15.6466,0.418,7534000,2024-04-23T05:00:01.\\n5510456,15.6466,-1.0,9818100,2024-04-23T05:00:01.\\n6038888,15.6466,-1.0,9965000,2024-04-23T05:00:01.\\n5941356,15.6466,0.0,20254600,2024-04-23T05:00:01.\\n5510456,15.6466,0.682,9989300,2024-04-23T05:00:01.\\n5026787,15.6466,0.0,12805200,2024-04-23T05:00:01.\\n5510456,15.6466,0.0,12652800,2024-04-23T05:00:01.\\n \\n Output: \\n" ]
{"power": "Y70Tlv14K3Y"}
tablejoin
2024-06-24T00:00:00
cb29bb1e6915d8366ff58783e47c9939d3d30712f2643cd23d6cbecc4210a2b2
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: training_title,training_type,training_description,training_provider,target_audience\\nAdvanced Data Analys,Online Class,Topics Include: Piv,Smartforce,\\nCulture and Its Effe,Online Class,Effective communicat,SkillSoft,\\nCisco SECURE 1.0: Ad,Online Class,In an Open Systems I,SkillSoft,\\nCustom Controls and ,Online Class,Developers often nee,SkillSoft,\\nCisco TVOICE 8.0: Tr,Online Class,The conference bridg,SkillSoft,\\nConfigure Terminal S,Online Class,\"Windows Server 2008,\",SkillSoft,\\n11 - Intel Property ,Online Class,,Bureau of Economic G,\\nCISM 2012: Informati,Online Class,Preparing incident r,SkillSoft,\\nAccounting for Sales,Online Class,Returns are an expec,SkillSoft,\\nCustomer Interaction,Online Class,Failing to realize t,SkillSoft,\\nCompressed Gas Safet,Online Class,Many industrial and ,SkillSoft,\\nCisco CWLF 1.0 Instr,Online Class,This course is part ,SkillSoft,\\nCommunicating Succes,Online Class,When you start worki,SkillSoft,\\nCISM 2012: Informati,Online Class,Information security,SkillSoft,\\nAdobe® Premiere® Ele,Online Class,Understanding the di,SkillSoft,\\n \\n CSV Table B: sNKw3v+J9DY,I2/J6hhVbCs,DMg+ND8pojM,o9rYtCP+WBg\\nOver the last 50 yea,,SkillSoft,15.6466\\nSection 508 requires,-,Smartforce,15.6466\\nWindows Forms and Wi,,SkillSoft,15.6466\\nCompTIA Security+ 20,,SkillSoft,15.6466\\nWhether you are a ho,,SkillSoft,15.6466\\nSolutions to busines,,SkillSoft,15.6466\\nTo recognize the fea,,Smartforce,15.6466\\nBuilding profitable ,,SkillSoft,15.6466\\nUsing Access macros ,,SkillSoft,15.6466\\nTo finalize and dist,,Smartforce,15.6466\\nThe Cisco ASA adapti,,SkillSoft,15.6466\\nTo describe how to u,,Smartforce,15.6466\\nWindows Vista replac,,SkillSoft,15.6466\\nThis course is part ,,SkillSoft,15.6466\\n,,QED/GLS,15.6466\\nTo recognize how thr,,Smartforce,15.6466\\n \\n Output: \\n" ]
{"training_description": "sNKw3v+J9DY", "target_audience": "I2/J6hhVbCs", "training_provider": "DMg+ND8pojM"}
tablejoin
2024-06-24T00:00:00
2e645a9a481f16ce14b5d069b62520852babd3b55383e00a75f675707088fddc
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: :@computed_region_dqjc_k29y,:@computed_region_jdnu_jmst,:@computed_region_5d9v_6bui,permitnum,worktype,applicationtype,location,:@computed_region_mfuy_bee2,:@computed_region_2fpw_swv9,:@computed_region_9p4x_9cjt\\n16.0,78.0,26.0,BLD2023-08018,Residential,Building,{'latitude': '40.785,19.0,19.0,350.0\\n12.0,78.0,26.0,BLD2023-08311,Residential,Building,{'latitude': '40.777,19.0,19.0,582.0\\n12.0,70.0,26.0,BLD2023-07867,Residential,Building,{'latitude': '40.759,19.0,24.0,567.0\\n12.0,71.0,26.0,BLD2023-02507,Residential,Building,{'latitude': '40.762,19.0,21.0,567.0\\n1.0,77.0,26.0,BLD2023-07072,Commercial,Building,{'latitude': '40.782,19.0,18.0,367.0\\n1.0,72.0,26.0,BLD2023-08689,Commercial,Building,{'latitude': '40.735,19.0,21.0,364.0\\n24.0,97.0,26.0,BLD2023-06295,Residential,Building,{'latitude': '40.708,19.0,27.0,245.0\\n12.0,72.0,26.0,BLD2023-05359,Residential,Building,{'latitude': '40.738,19.0,21.0,472.0\\n16.0,80.0,26.0,BLD2023-06139,Commercial,Building,{'latitude': '40.808,19.0,18.0,278.0\\n12.0,78.0,26.0,BLD2023-07750,Commercial,Building,{'latitude': '40.770,19.0,19.0,240.0\\n \\n CSV Table B: v02+v1698aE,ZswU2nie504,q6rFvdGN4F0,sXpNMhZkCLA,R1VkE8XKb0E,+nTxjQhBWmY,a8tgQid0Dvs,AJ7cmCm31yg\\nNo,Building,{'latitude': '40.739,26.0,472.0,19.0,BLD2023-08495,21.0\\nNo,Building,{'latitude': '40.738,26.0,358.0,19.0,BLD2023-04923,26.0\\nNo,Building,{'latitude': '40.715,26.0,384.0,19.0,BLD2023-07730,27.0\\nNo,Building,{'latitude': '40.733,26.0,360.0,19.0,BLD2023-07089,24.0\\nNo,Building,{'latitude': '40.786,26.0,352.0,19.0,BLD2023-04229,18.0\\nSi,Building,{'latitude': '40.749,26.0,361.0,19.0,BLD2023-08476,20.0\\nSi,Building,{'latitude': '40.739,26.0,474.0,19.0,BLD2023-05808,20.0\\nSi,Building,{'latitude': '40.785,26.0,350.0,19.0,BLD2023-08019,19.0\\nNo,Building,{'latitude': '40.725,26.0,277.0,19.0,BLD2023-03316,27.0\\nNo,Building,{'latitude': '40.784,26.0,495.0,19.0,BLD2023-04556,18.0\\nSi,Building,{'latitude': '40.714,26.0,573.0,19.0,BLD2023-07673,27.0\\n \\n Output: \\n" ]
{"location": "q6rFvdGN4F0", "applicationtype": "ZswU2nie504", ":@computed_region_mfuy_bee2": "+nTxjQhBWmY", ":@computed_region_5d9v_6bui": "sXpNMhZkCLA", ":@computed_region_2fpw_swv9": "AJ7cmCm31yg", "permitnum": "a8tgQid0Dvs", ":@computed_region_9p4x_9cjt": "R1VkE8XKb0E"}
tablejoin
2024-06-24T00:00:00
539fd06729e1f852302dd51aab15ffa115225362425ef04808cdef88d000d300
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: cleanup_site_name,location,zipcode,city,responsible_section,:@computed_region_fny7_vc3j,:@computed_region_x4ys_rtnd,region,latitude,cleanup_site_id\\nRAINBOW MINI MART,{'latitude': '47.528,98815,CASHMERE,Central,8,2956.0,Central,47.528331,11012\\nLake Chelan SD Athle,{'latitude': '47.842,98816,CHELAN,Central,8,2956.0,Central,47.842097,1448\\nGRAMOR DEVELOPMENT,{'latitude': '45.641,98661-6548,VANCOUVER,Southwest,3,2977.0,Southwest,45.64106,4871\\nASTRO MINIT MART 726,{'latitude': '45.614,98661,VANCOUVER,Southwest,3,2977.0,Southwest,45.614722,905\\nSequim RV Park,{'latitude': '48.023,98382,SEQUIM,Southwest,6,2976.0,Southwest,48.023378,7714\\nRichland Uptown Shop,{'latitude': '46.288,99354,RICHLAND,Central,4,2955.0,Central,46.28863,11640\\nMidland Trucking,{'latitude': '47.480,98801,WENATCHEE,Central,8,2956.0,Central,47.480129,11504\\nEXHAUST SHOP,{'latitude': '48.116,98362-3111,PORT ANGELES,Southwest,6,2976.0,Southwest,48.11676,7775\\nUS DOE 100-DR-2,{'latitude': '46.688,99352,RICHLAND,Nuclear Waste Prgm,4,2955.0,Central,46.688728,4610\\nEastmont Junior High,{'latitude': '47.416,98802,EAST WENATCHEE,Central,8,2979.0,Central,47.41673,1904\\nBNRR PROSSER MICROWA,{'latitude': '46.208,99350,PROSSER,Central,4,2955.0,Central,46.208744,10066\\nUSFS CHELATCHIE PRAI,{'latitude': '45.926,98601-9715,AMBOY,Headquarters,3,2977.0,Southwest,45.92699,8623\\nPacific Rim Land,{'latitude': '47.620,98801,OLDS STATION,Central,8,2956.0,Central,47.6203,593\\nWillard Aldridge & A,{'latitude': '47.418,98801,WENATCHEE,Central,8,2956.0,Central,47.418403,3282\\nGRACES CLEANERS,{'latitude': '45.780,98604,Battle Ground,Southwest,3,2977.0,Southwest,45.780563,578\\nUS DOE 100-HR-2,{'latitude': '46.699,99352,RICHLAND,Nuclear Waste Prgm,4,2955.0,Central,46.699242,2989\\nTIME OIL HANDY ANDY ,{'latitude': '45.653,98663-2187,VANCOUVER,Southwest,3,2977.0,Southwest,45.65333,4981\\n \\n CSV Table B: /8WN7SwQxtM,IBOO7n66j2I,sK4/vfuebl0,+TcFRhetc3o,xEEeWKcl26k,aFVTAGS5OJI,MVALsqWWTVY,cVvd7+Y4m6s,0bFLf6WxD8A,yxJQbHxz2Ew\\ngas,Weak,No,6040452,0,{'latitude': '45.587,3,11792,15.6466,726 NE 5TH AVE CAMAS\\ngas,Weak,No,6038888,0,{'latitude': '46.975,6,5218,15.6466,SUNSHINE CAR WASH\\ngas,Weak,No,5941356,0,{'latitude': '46.285,4,7512,15.6466,MCCUES TEXACO\\ngas,New,No,6040452,0,{'latitude': '48.119,6,9873,15.6466,LOG CABIN RESORT\\ngas,Weak,No,5941356,0,{'latitude': '46.234,4,1497,15.6466,Lithia Ford of Tri C\\ngas,New,Si,5510456,0,{'latitude': '48.123,6,1301,15.6466,PORT ANGELES PORT OF\\ngas,New,Si,6040452,0,{'latitude': '45.578,3,2482,15.6466,HAMBLETON BROS LOG Y\\ngas,New,Si,5510456,0,{'latitude': '47.050,6,330,15.6466,North Beach PAWS She\\ngas,Weak,No,6038888,0,{'latitude': '45.571,3,4118,15.6466,Cascade Paint\\ngas,New,No,5026787,0,{'latitude': '45.636,3,9558,15.6466,ABANDON TANK SITE\\ngas,New,Si,6040452,0,{'latitude': '46.274,4,6112,15.6466,Columbia Oil Company\\ngas,Weak,No,5510456,0,{'latitude': '48.107,6,1649,15.6466,TRUCK TOWN 1921 HWY \\ngas,Weak,Si,6038888,0,{'latitude': '46.118,3,1539,15.6466,TRANSMISSION TRADING\\ngas,Good,Si,5941356,0,{'latitude': '45.671,3,273,15.6466,Boomsnub Inc\\ngas,New,No,5510456,0,{'latitude': '46.815,4,6952,15.6466,UNOCAL BULK PLANT 05\\ngas,Weak,No,5026787,0,{'latitude': '46.213,4,14385,15.6466,Oil Re Refining Comp\\ngas,New,No,5510456,0,{'latitude': '48.104,6,4517,15.6466,MANKE LOG YARD\\n \\n Output: \\n" ]
{"location": "aFVTAGS5OJI", "cleanup_site_id": "cVvd7+Y4m6s", "cleanup_site_name": "yxJQbHxz2Ew", ":@computed_region_fny7_vc3j": "MVALsqWWTVY"}
tablejoin
2024-06-24T00:00:00
a50e16a7dec04c766f864754305d6b28a99fe54602c7c913c525c067c405d279
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Vehicle_Model,Mileage,Maintenance_History,Reported_Issues,Vehicle_Age,Fuel_Type,Transmission_Type,Engine_Size,Odometer_Reading,Last_Service_Date\\nVan,61745,Poor,1,1,Petrol,Manual,2000,145019,2023-10-19\\nBus,58742,Average,2,7,Diesel,Manual,2000,130003,2023-12-18\\nMotorcycle,57412,Good,3,10,Diesel,Manual,800,139794,2023-11-15\\nCar,43158,Good,1,2,Electric,Automatic,800,51215,2023-10-04\\nVan,73695,Average,3,2,Electric,Automatic,1000,15453,2023-04-09\\nTruck,43662,Good,1,8,Petrol,Automatic,2500,70976,2023-05-16\\nVan,42638,Average,0,10,Electric,Manual,800,46541,2023-08-02\\nSUV,50613,Average,2,2,Electric,Automatic,1500,101947,2023-07-23\\nCar,31839,Good,4,10,Diesel,Automatic,2500,137976,2023-10-05\\nBus,72112,Average,2,5,Diesel,Automatic,800,110035,2024-02-23\\nSUV,73526,Average,1,8,Diesel,Automatic,2000,61287,2023-04-16\\n \\n CSV Table B: ZxQEcZfVyiA,4lnA15H3a94,O5PnzZQwWvU,YbimjSBeMkI,t8DtGa8xUVw,iZrkpx1ubOo\\nManual,39324,5,Bus,0,2024-01-07\\nManual,65451,3,Van,0,2023-09-08\\nManual,131118,2,SUV,0,2024-01-24\\nAutomatic,148084,3,Van,0,2023-07-13\\nAutomatic,66820,2,SUV,0,2023-07-05\\nAutomatic,66707,2,Motorcycle,0,2023-11-27\\nAutomatic,117639,5,Van,0,2023-07-05\\nAutomatic,97214,5,Truck,0,2024-02-11\\nAutomatic,11947,0,Motorcycle,0,2023-07-28\\nAutomatic,124606,4,SUV,0,2023-05-31\\nAutomatic,30057,0,SUV,0,2024-02-07\\n \\n Output: \\n" ]
{"Odometer_Reading": "4lnA15H3a94", "Vehicle_Model": "YbimjSBeMkI", "Last_Service_Date": "iZrkpx1ubOo", "Reported_Issues": "O5PnzZQwWvU", "Transmission_Type": "ZxQEcZfVyiA"}
tablejoin
2024-06-24T00:00:00
75fca1a433c6e663241c1941e6034cd7625cd4b5981159c7f4ad74703df98b53
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Outlook,Temperature,Humidity,Wind,Play_Badminton\\nRain,Cool,Normal,Weak,No\\nOvercast,Cool,Normal,Weak,Yes\\nSunny,Mild,Normal,Strong,No\\nRain,Mild,High,Strong,No\\nOvercast,Mild,High,Weak,Yes\\nRain,Cool,Normal,Strong,No\\nRain,Cool,High,Weak,No\\nOvercast,Hot,High,Strong,No\\nOvercast,Hot,High,Weak,Yes\\nRain,Hot,High,Strong,No\\nRain,Cool,High,Strong,No\\nSunny,Hot,High,Strong,No\\nRain,Mild,Normal,Weak,No\\nRain,Hot,Normal,Weak,No\\nOvercast,Hot,Normal,Weak,Yes\\nRain,Mild,Normal,Strong,No\\nOvercast,Hot,Normal,Strong,No\\n \\n CSV Table B: ijAq03/9VNE,9etcI5xa42c,/8WN7SwQxtM,YvXYPZhNyxA\\nWeak,2024-04-23T05:00:01.,gas,Sunny\\nStrong,2024-04-23T05:00:01.,gas,Sunny\\nWeak,2024-04-23T05:00:01.,gas,Sunny\\nWeak,2024-04-23T05:00:01.,gas,Sunny\\nStrong,2024-04-23T05:00:01.,gas,Sunny\\nStrong,2024-04-23T05:00:01.,gas,Sunny\\nWeak,2024-04-23T05:00:01.,gas,Overcast\\nStrong,2024-04-23T05:00:01.,gas,Rain\\nWeak,2024-04-23T05:00:01.,gas,Rain\\nStrong,2024-04-23T05:00:01.,gas,Sunny\\nWeak,2024-04-23T05:00:01.,gas,Sunny\\nStrong,2024-04-23T05:00:01.,gas,Overcast\\nStrong,2024-04-23T05:00:01.,gas,Overcast\\nWeak,2024-04-23T05:00:01.,gas,Overcast\\nWeak,2024-04-23T05:00:01.,gas,Rain\\nWeak,2024-04-23T05:00:01.,gas,Sunny\\nWeak,2024-04-23T05:00:01.,gas,Sunny\\n \\n Output: \\n" ]
{"Outlook": "YvXYPZhNyxA", "Wind": "ijAq03/9VNE"}
tablejoin
2024-06-24T00:00:00
140b7ab87b7be33e80fff3cfc052077d34cc51b5038c1c390cfb9780ad948c04
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: :@computed_region_dqjc_k29y,:@computed_region_jdnu_jmst,:@computed_region_5d9v_6bui,permitnum,worktype,applicationtype,location,:@computed_region_mfuy_bee2,:@computed_region_2fpw_swv9,:@computed_region_9p4x_9cjt\\n12.0,68.0,26.0,BLD2023-07925,Residential,Building,{'latitude': '40.738,19.0,24.0,73.0\\n12.0,72.0,26.0,BLD2023-05473,Commercial,Building,{'latitude': '40.738,19.0,21.0,472.0\\n24.0,68.0,26.0,BLD2023-07876,Residential,Building,{'latitude': '40.735,19.0,24.0,360.0\\n16.0,80.0,26.0,BLD2023-02640,Commercial,Building,{'latitude': '40.801,19.0,18.0,278.0\\n1.0,72.0,26.0,BLD2023-08689,Commercial,Building,{'latitude': '40.735,19.0,21.0,364.0\\n1.0,80.0,26.0,BLD2023-03353,Residential,Building,{'latitude': '40.780,19.0,18.0,12.0\\n16.0,80.0,26.0,BLD2023-07162,Residential,Building,{'latitude': '40.785,19.0,18.0,352.0\\n12.0,113.0,26.0,BLD2023-06120,Residential,Building,{'latitude': '40.748,19.0,20.0,361.0\\n12.0,78.0,26.0,BLD2023-08556,Residential,Building,{'latitude': '40.788,19.0,19.0,366.0\\n23.0,68.0,26.0,BLD2023-08383,Commercial,Building,{'latitude': '40.731,19.0,24.0,243.0\\n \\n CSV Table B: sXpNMhZkCLA,Jez514k++0Q,AVoxAgMZHug,SfVC0olx/OE,t8DtGa8xUVw,tKc+06TrJ9c,PMUacJBoTFo,+I7cBfMYFoQ\\n26.0,6040452,355.0,24591000,0,12.0,{'latitude': '40.764,15.6466\\n26.0,6038888,469.0,8334800,0,12.0,{'latitude': '40.781,15.6466\\n26.0,5941356,122.0,9875400,0,12.0,{'latitude': '40.772,15.6466\\n26.0,6040452,361.0,8338300,0,12.0,{'latitude': '40.747,15.6466\\n26.0,5941356,239.0,8995500,0,1.0,{'latitude': '40.799,15.6466\\n26.0,5510456,567.0,8564500,0,12.0,{'latitude': '40.755,15.6466\\n26.0,6040452,474.0,8948500,0,24.0,{'latitude': '40.738,15.6466\\n26.0,5510456,70.0,11859900,0,12.0,{'latitude': '40.774,15.6466\\n26.0,6038888,367.0,16537400,0,1.0,{'latitude': '40.792,15.6466\\n26.0,5026787,71.0,11010400,0,12.0,{'latitude': '40.752,15.6466\\n26.0,6040452,582.0,7534000,0,16.0,{'latitude': '40.782,15.6466\\n \\n Output: \\n" ]
{":@computed_region_dqjc_k29y": "tKc+06TrJ9c", ":@computed_region_5d9v_6bui": "sXpNMhZkCLA", "location": "PMUacJBoTFo", ":@computed_region_9p4x_9cjt": "AVoxAgMZHug"}
tablejoin
2024-06-24T00:00:00
5063b77b06647a10818a76a2feda884741860ca4ef5816ae4580babafea11fb0
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Symptom,Remedy,RemedyStrength,Part_of_remedy,Final_remedy\\nAbdominal respiratio,Thuj.,1,True,False\\nRattling,Sep.,2,True,False\\nSnoring,Nit-ac.,1,False,False\\nSobbing,Nit-ac.,1,False,False\\nLoud respiration,Squil.,1,True,False\\nGasping,Merc.,1,False,False\\nIrregular respiratio,Calad.,1,False,False\\nImperceptible respir,Ars.,2,True,True\\nRough respiration,Plb.,1,True,False\\nSighing,Tax.,1,False,False\\n\"Impeded,obstructed r\",Abrot.,2,False,False\\nSlow respiration,Asaf.,2,False,False\\nSlow respiration,Colch.,2,False,False\\nHot breath,Cann-s.,1,False,False\\nDifficult respiratio,Carb-v.,1,False,False\\nLoud respiration,Ars.,1,True,False\\n\"Impeded,obstructed r\",Puls.,1,False,False\\n \\n CSV Table B: tsBRUXdOa3Q,JT9OTPbY4r4,0bFLf6WxD8A,Xl360xlCCTk\\nPlan.,True,15.6466,False\\nCalc.,False,15.6466,False\\nStram.,True,15.6466,True\\nCanth.,False,15.6466,False\\nColch.,False,15.6466,False\\nKali-i.,False,15.6466,False\\nNit-ac.,True,15.6466,False\\nSulf.,True,15.6466,False\\nColoc.,False,15.6466,False\\nBry.,True,15.6466,True\\nOp.,False,15.6466,False\\nNux-m.,True,15.6466,True\\nSquil.,True,15.6466,False\\nHep.,True,15.6466,False\\nBell.,True,15.6466,True\\nSpong.,True,15.6466,False\\nCarb-v.,True,15.6466,False\\n \\n Output: \\n" ]
{"Part_of_remedy": "JT9OTPbY4r4", "Final_remedy": "Xl360xlCCTk", "Remedy": "tsBRUXdOa3Q"}
tablejoin
2024-06-24T00:00:00
ac146c48d703160bded02521568583372fc6b10bdbd98f36f57fcff7d0790d10
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: id,original_text,rewritten_text,rewrite_prompt\\n295,Report: Smoke was de,\"Bewilderingly, smoke\",Use more complex and\\n243,\"Hey Julia, just want\",\"Hi Julia, please sen\",La différence est de\\n249,Marcia blamed hersel,\"Marcia, the petition\",Use a more formal an\\n81,Subject: Urgent Fold,Subject: Timeless Ca,Revise the text to h\\n186,Ladies and gentlemen,Ladies and gentlemen,Include a somber not\\n198,\"Once upon a time, in\",\"Once in Oakville, Mi\",Summarize the story \\n298,\"Nathan, a renowned h\",\"Nathan, a ruthless h\",Add an unexpected tw\\n155,\"Marilyn, a strugglin\",\"Marilyn, a talented \",Make the text more c\\n59,\"Hi Christopher, coul\",Hey Christopher! Can,Revise the text to a\\n9,\"Today, Angela and I \",\"Today, Angela and I \",Revise the text with\\n192,\"Hi Eva, \\\\n\\\\nJust wan\",\"Hi Eva, \\\\n\\\\nI hope t\",Revise the text with\\n352,\"December 24, 2021: S\",\"December 24, 2021: A\",Elevate the tone and\\n330,Rebecca eagerly awai,Rebecca cautiously a,Reflect a more cauti\\n175,Hey Robert! I just h,\"Hey Robert, remember\",Reframe the invitati\\n123,Ladies and gentlemen,Ladies and gentlemen,Include a health adv\\n166,\"Today, while on safa\",\"Today, during my enc\",Revise the text with\\n214,\"Dear Anibal,\\\\n\\\\nI ho\",\"Dear Anibal,\\\\n\\\\nI fo\",La diferencia es red\\n \\n CSV Table B: xEEeWKcl26k,/8WN7SwQxtM,3i4QkTML4G0,9etcI5xa42c\\n0,gas,Hey Esther! Did you ,2024-04-23T05:00:01.\\n0,gas,\"Anna, cradling her r\",2024-04-23T05:00:01.\\n0,gas,\"Dear Mr. Johnson,\\\\n\\\\\",2024-04-23T05:00:01.\\n0,gas,Ladies and gentlemen,2024-04-23T05:00:01.\\n0,gas,\"Today, James and I i\",2024-04-23T05:00:01.\\n0,gas,Title: Buffalo Bonan,2024-04-23T05:00:01.\\n0,gas,75% of people believ,2024-04-23T05:00:01.\\n0,gas,Remove the squatter ,2024-04-23T05:00:01.\\n0,gas,\"Hi Sara, \\\\n\\\\nI hope \",2024-04-23T05:00:01.\\n0,gas,Hey Charles! Remembe,2024-04-23T05:00:01.\\n0,gas,In a world where tru,2024-04-23T05:00:01.\\n0,gas,\"Walter, a farmer, fo\",2024-04-23T05:00:01.\\n0,gas,\"Today, I bought fres\",2024-04-23T05:00:01.\\n0,gas,Through every strugg,2024-04-23T05:00:01.\\n0,gas,\"In Eldoria, Kevin as\",2024-04-23T05:00:01.\\n0,gas,\"Jerry, a gifted musi\",2024-04-23T05:00:01.\\n0,gas,Journal Entry - Acco,2024-04-23T05:00:01.\\n \\n Output: \\n" ]
{"rewritten_text": "3i4QkTML4G0"}
tablejoin
2024-06-24T00:00:00
10047d040ef1e563f1db3278979d56d1182617b3484c63ed53a388a0d006a7e4
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: id,dept_name,program_name,org_number,measure_name,measure_id,active,priority_measure,budget_book,fiscal_year\\n2,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2012-13\\n41,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2019-20\\n4,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2014-15\\n21,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2015-16\\n2,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2012-13\\n3,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2013-14\\n2,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2012-13\\n4,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2014-15\\n41,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2019-20\\n21,Department of Public,Public Works Adminis,4510B,Percent rating exper,5,YES,YES,NO,FY 2015-16\\n \\n CSV Table B: aWH6IJ5IjF4,hMlFRB3b0OU,6TBG45I7TLk,UCUt++OaxnM,Gu1a6Jx2RSE,0dfsuiTLoSQ,tTar7XACrwc,53NiJOr4DrA,T2n+8bg76ww\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2015-16,0,4510B,5,YES,No\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2013-14,1,4510B,5,YES,No\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2013-14,2,4510B,5,YES,No\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2013-14,3,4510B,5,YES,No\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2018-19,4,4510B,5,YES,No\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2011-12,5,4510B,5,YES,Si\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2011-12,6,4510B,5,YES,Si\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2018-19,7,4510B,5,YES,Si\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2019-20,8,4510B,5,YES,No\\nDepartment of Public,NO,2024-04-23T05:00:01.,FY 2013-14,9,4510B,5,YES,No\\n \\n Output: \\n" ]
{"dept_name": "aWH6IJ5IjF4", "fiscal_year": "UCUt++OaxnM", "measure_id": "tTar7XACrwc", "priority_measure": "53NiJOr4DrA", "budget_book": "hMlFRB3b0OU", "org_number": "0dfsuiTLoSQ"}
tablejoin
2024-06-24T00:00:00
a8995a220d4b23e751dded30067eb09897b7269b0ec3632762c9e97d41b80c95
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Date,Open,High,Low,Close,Volume\\n2013-01-04,42.459999,42.5,41.82,41.970001,15428500\\n2013-12-18,47.869999,48.93,47.650002,48.900002,13549700\\n2013-09-18,47.810001,48.709999,47.630001,48.400002,14008700\\n2015-04-27,57.830002,58.029999,56.880001,57.099998,10599600\\n2015-07-06,57.240002,57.84,56.639999,57.549999,8054100\\n2015-11-16,52.189999,53.810001,52.130001,53.700001,6907800\\n2014-03-10,57.439999,57.619999,57.0,57.32,7383200\\n2014-12-16,56.970001,58.290001,56.779999,56.799999,11214000\\n2015-12-15,52.48,53.189999,52.23,52.900002,11585900\\n2013-11-20,47.98,48.419998,47.75,48.130001,8251900\\n2014-08-08,55.869999,56.610001,55.580002,56.549999,7081500\\n2014-11-04,58.869999,59.709999,58.869999,59.369999,11338400\\n2012-11-12,44.470001,44.52,43.880001,44.02,7329800\\n2014-12-22,59.119999,59.560001,58.549999,58.959999,10010500\\n2014-01-27,52.860001,54.099998,52.529999,52.529999,31002000\\n2014-02-07,53.650002,54.82,53.439999,54.77,14497100\\n2013-07-05,46.93,47.299999,46.610001,47.16,8103000\\n \\n CSV Table B: uUeSJYWTyDY,sK4/vfuebl0,9etcI5xa42c\\n14656200,No,2024-04-23T05:00:01.\\n11893000,No,2024-04-23T05:00:01.\\n7429500,No,2024-04-23T05:00:01.\\n14065400,No,2024-04-23T05:00:01.\\n14165400,No,2024-04-23T05:00:01.\\n8649500,Si,2024-04-23T05:00:01.\\n12117800,Si,2024-04-23T05:00:01.\\n9935100,Si,2024-04-23T05:00:01.\\n5187600,No,2024-04-23T05:00:01.\\n14206900,No,2024-04-23T05:00:01.\\n6900000,Si,2024-04-23T05:00:01.\\n8981200,No,2024-04-23T05:00:01.\\n9639700,Si,2024-04-23T05:00:01.\\n8654800,Si,2024-04-23T05:00:01.\\n7914600,No,2024-04-23T05:00:01.\\n7533400,No,2024-04-23T05:00:01.\\n8617800,No,2024-04-23T05:00:01.\\n \\n Output: \\n" ]
{"Volume": "uUeSJYWTyDY"}
tablejoin
2024-06-24T00:00:00
8b842182b7cbb2b961d8cdc64a1b4b28aff1f8ed4f4dd3fb58e3533baa754043
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: DeviceTimeStamp,WL1,WL2,WL3,VAL1,VAL2,VAL3,RVAL1,RVAL2,RVAL3\\n2019-09-12T16:45,32.1,27.7,34.0,32.9,28.1,34.4,7.0,4.5,0.0057\\n2020-02-23T03:00,9.6,3.4,11.0,9.6,3.4,11.1,0.2,0.2,0.0017\\n2020-03-26T03:15,10.9,7.5,12.0,10.9,7.8,12.1,0.4,2.0,0.0011\\n2019-08-12T20:15,32.0,37.3,36.4,32.1,37.4,36.8,2.1,2.6,0.0051\\n2020-04-04T08:30,11.6,8.9,11.4,11.7,9.5,12.1,1.9,3.3,0.004\\n2019-08-22T09:45,16.2,13.2,17.6,16.2,13.7,18.4,0.8,3.5,0.0053\\n2019-09-17T23:00,21.6,19.2,30.2,21.9,19.3,30.3,3.5,1.9,0.0012\\n2019-12-05T06:45,8.3,6.1,12.0,8.4,6.2,12.7,-0.4,1.5,0.004\\n2019-09-14T21:15,24.6,25.9,27.9,24.8,25.9,28.1,2.5,1.7,0.0035\\n2019-10-25T23:43,14.5,10.1,15.8,14.7,10.3,16.2,2.0,1.7,0.0036\\n2019-12-14T08:00,7.6,8.1,11.8,7.7,8.6,12.4,0.9,2.8,0.0037\\n2020-03-30T23:15,21.3,12.5,19.7,21.4,12.7,20.0,1.7,2.2,0.0034\\n2020-04-13T12:15,11.9,6.7,15.5,12.0,7.1,16.1,0.8,2.2,0.0043\\n2020-04-09T00:45,13.4,10.1,16.3,13.5,10.3,16.4,1.0,1.9,0.0022\\n2019-08-14T19:30,27.9,32.3,39.6,27.9,32.4,40.0,1.1,3.2,0.0054\\n2020-04-07T05:15,13.1,7.5,15.2,13.1,7.7,15.4,-0.2,1.7,0.0024\\n2020-01-28T13:45,17.1,11.3,20.6,17.2,11.5,21.0,1.4,2.3,0.0043\\n2020-04-08T01:30,15.6,10.4,19.2,15.6,10.5,19.3,0.0,1.4,0.002\\n2019-10-19T12:45,35.7,24.3,28.2,35.9,24.5,28.9,3.8,3.2,0.0066\\n \\n CSV Table B: 5VcgIh9wM7I,S3GJlnNyunE,v3NEVV2Owbs,pQZDnCfGEk4,ega9e6/dBuw,mlTxGdesaBg,09ii68KGAcU\\n25.7,25.0,0,gas,22.1,No,6040452\\n13.4,13.2,1,gas,9.5,No,6038888\\n26.7,26.4,2,gas,19.8,No,5941356\\n27.0,26.2,3,gas,20.7,No,6040452\\n13.6,13.3,4,gas,9.8,No,5941356\\n21.6,21.6,5,gas,19.3,Si,5510456\\n18.9,18.7,6,gas,20.7,Si,6040452\\n7.6,7.1,7,gas,9.7,Si,5510456\\n27.7,26.5,8,gas,34.3,No,6038888\\n13.7,13.5,9,gas,9.8,No,5026787\\n21.4,20.9,10,gas,15.0,Si,6040452\\n14.1,13.9,11,gas,12.7,No,5510456\\n12.0,11.7,12,gas,10.6,Si,6038888\\n12.4,12.2,13,gas,9.3,Si,5941356\\n26.4,26.0,14,gas,19.2,No,5510456\\n9.9,9.6,15,gas,7.8,No,5026787\\n23.5,23.1,16,gas,14.4,No,5510456\\n0.0,0.0,17,gas,0.0,No,5026787\\n16.1,16.1,18,gas,12.9,No,5510456\\n15.8,15.4,19,gas,12.4,No,6038888\\n \\n Output: \\n" ]
{"WL1": "ega9e6/dBuw", "VAL3": "5VcgIh9wM7I", "WL3": "S3GJlnNyunE"}
tablejoin
2024-06-24T00:00:00
dc753a46614f7f4d1c839d06ec864324f8b6142e30bf804dae6aae8b6eb91941
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: source_name,source_link,event_id,event_date,event_title,event_description,location_description,location_accuracy,landslide_category,landslide_trigger\\nstuff,{\\'url\\': \\'http://www.,3931,2011-08-17T23:45:00.,\"Belvedere Road, Hata\",\"landslide, about 15m\",\"Belvedere Road, Hata\",exact,landslide,unknown\\ncnn,{\\'url\\': \\'http://www.,1621,2010-04-06T00:00:00.,other slides in Rio ,Brazilian President ,other slides in Rio ,50km,complex,downpour\\nCBS News,{\\'url\\': \\'https://www,973,2007-01-19T00:00:00.,\"San Ramon district, \",(CBS/AP) At least 10,\"San Ramon district, \",10km,landslide,downpour\\ngoogle,{\\'url\\': \\'http://www.,1594,2010-03-26T00:00:00.,\"Carabaya Province, P\",Peruvian police say ,\"Carabaya Province, P\",unknown,landslide,downpour\\nthecitizen.co,{\\'url\\': \\'http://thec,1293,2009-11-10T00:00:00.,\"Goha village, Same d\",A landslide on a mou,\"Goha village, Same d\",25km,landslide,downpour\\nAP.google.com,{\\'url\\': \\'http://ap.g,325,2007-10-26T00:00:00.,Kinshasa,heavy flooding and l,Kinshasa,25km,mudslide,rain\\nthejakartapost,{\\'url\\': \\'http://www.,3384,2011-04-20T01:00:00.,\"Rengganis(?), Cintam\",\"Wed, 04/20/2011 1:19\",\"Rengganis(?), Cintam\",50km,landslide,downpour\\nantaranews,{\\'url\\': \\'http://www.,4617,2012-11-18T00:00:00.,\"Caringin, Sukabumi\",Landslides have hit ,\"Caringin, Sukabumi\",5km,landslide,rain\\nLa depeche de Madaga,{\\'url\\': \\'http://www.,9648,2016-05-13T00:00:00.,\"Manjavela, in the di\",\"On Friday, a tragedy\",\"Manjavela, in the di\",50km,other,unknown\\nStandard Digital,{\\'url\\': \\'http://www.,7101,2015-05-01T18:00:00.,Maganyakulo area of ,\"\"\"It was around 6p.m.\",Maganyakulo area of ,5km,landslide,continuous_rain\\nnews.bbc,{\\'url\\': \\'http://news,1376,2009-12-31T00:00:00.,Greater Rio de Janei,Heavy rains have cau,Greater Rio de Janei,5km,mudslide,downpour\\nStuff,{\\'url\\': \\'http://www.,1881,2010-05-20T09:00:00.,\"the narrows, near Bo\",A landslide that dum,\"the narrows, near Bo\",5km,rock_fall,continuous_rain\\nNTD Television,{\\'url\\': \\'https://web,1476,2010-02-06T00:00:00.,Zurite district,Mud and rocks piled ,Zurite district,10km,mudslide,downpour\\necr,{\\'url\\': \\'http://www.,4542,2012-09-06T00:00:00.,Amanzimtoti,Clean-up operations ,Amanzimtoti,10km,landslide,downpour\\nlivinginperu,{\\'url\\': \\'http://www.,1366,2009-12-17T00:00:00.,\"Huamanga, Ayacucho, \",The Presidency of Pe,\"Huamanga, Ayacucho, \",25km,mudslide,downpour\\nwellington.scoop.co.,{\\'url\\': \\'http://well,4816,2013-04-21T00:00:00.,\"Takaka Hill Highway,\",Torrential rain has ,\"Takaka Hill Highway,\",25km,landslide,rain\\n \\n CSV Table B: yYHA7vnvIBw,Zmb1BRco8l4,IbcRFtTB0wI,0F0qIGz9/W4,6kw4WhkPpNQ,5AxJyCWgWsc,o9rYtCP+WBg,jgFx2gX5+sM,vhKccO94mOM\\nNo,gas,unknown,Landslides have clos,Rex Highway between ,abc,15.6466,{\\'url\\': \\'http://www.,0\\nNo,gas,1km,PARTS of the Souther,\"New England Hwy, 800\",Warwick Daily News,15.6466,{\\'url\\': \\'http://www.,0\\nNo,gas,1km,O mapa da devastação,Cocota,maps.google.com,15.6466,{\\'url\\': \\'http://maps,0\\nNo,gas,10km,over 200 slips in pa,Manukau,3news.co,15.6466,{\\'url\\': \\'http://3new,0\\nNo,gas,25km,8 month old baby kil,\"Danyon village, Slah\",antara,15.6466,{\\'url\\': \\'http://www.,0\\nSi,gas,5km,The worst hit area w,Teresópolis,guardian,15.6466,{\\'url\\': \\'http://www.,0\\nSi,gas,250km,Heavy rains slammed ,Quellouno,RT,15.6466,,0\\nSi,gas,1km,A landslide in La Pa,Auquisamaña Area Lan,Buzz Videos,15.6466,{\\'url\\': \\'http://www.,0\\nNo,gas,1km,The landslip that ha,Snowy Mountains High,abc,15.6466,{\\'url\\': \\'http://www.,0\\nNo,gas,25km,The government yeste,Bikita Landslide Kil,Newsday,15.6466,{\\'url\\': \\'https://www,0\\nSi,gas,5km,A landslide in Bogor,\"Sempur, Bogor, West \",www.thejakartaglobe.,15.6466,{\\'url\\': \\'http://www.,0\\nNo,gas,5km,A LIFE could have be,\"Waimanu road, near S\",fijitimes,15.6466,{\\'url\\': \\'http://www.,0\\nSi,gas,1km,landslides on the ro,Estrada da Froes Nit,maps.google.com,15.6466,{\\'url\\': \\'http://maps,0\\nSi,gas,100km,The central jungle o,Satipo Province,Living In Peru,15.6466,{\\'url\\': \\'http://www.,0\\nNo,gas,1km,A remote village com,\"Biche, Gatokae, Moro\",Solomon Star,15.6466,{\\'url\\': \\'http://www.,0\\nNo,gas,10km,Eight people were ki,Resifi(Recife) north,english.ruvr,15.6466,{\\'url\\': \\'http://engl,0\\n \\n Output: \\n" ]
{"source_name": "5AxJyCWgWsc", "location_accuracy": "IbcRFtTB0wI", "event_description": "0F0qIGz9/W4", "source_link": "jgFx2gX5+sM", "event_title": "6kw4WhkPpNQ"}
tablejoin
2024-06-24T00:00:00
4840c0c5075383274db75d8610087c3a725f4be885832e5fa97a46933e7485ae
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: Areas,freq_1,freq_2,freq_3,freq_4,freq_5,freq_6\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n52.69691934980033,1.0,0.3066003914775975,0.1245689303063943,0.1054524435622401,0.0417304339140407,0.0547108674678267\\n7.185992410601374,1.0,0.2999206528073539,0.1222511487682431,0.0772947974051657,0.0487553884339519,0.0353324096055299\\n32.7291864913512,1.0,0.213146090194573,0.1183964102800875,0.0704606572262718,0.0441183363159674,0.033178644798613\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n6.446951236371171,1.0,0.4262288438201601,0.1916872539057724,0.1156817194523204,0.044848274171492,0.0222903737771126\\n1.957639593458942,1.0,0.533393886177141,0.1893246349211403,0.0714277935184967,0.0284848249671974,0.0238569282251618\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n71.00332161496897,1.0,0.2740220004756795,0.1278905256445208,0.0692331631443914,0.0482897713293649,0.0357922581591704\\n0.0,0.0,0.0,0.0,0.0,0.0,0.0\\n3.301667962759854,1.0,0.1091959612260343,0.0454704054003767,0.0344613292581027,0.025557057115189,0.0129898029281604\\n16.754123508406163,0.2856924485187471,0.1709920569783453,0.1496525553644551,0.0982513539490028,0.1027482655787128,0.1590234249293817\\n \\n CSV Table B: 7dYptJU3eKE,7raemdfhCtY,oSIrzv9LNvo,NDJjzG/U34g,j5ilz2RtsY4\\n24591000,No,15.6466,0.0,0.0\\n8334800,No,15.6466,0.0,0.0\\n9875400,No,15.6466,0.0,0.0\\n8338300,No,15.6466,0.0,0.0\\n8995500,No,15.6466,0.0,0.0\\n8564500,Si,15.6466,0.1795146403862751,0.5059258063362236\\n8948500,Si,15.6466,0.05852812458766,0.0248499329639729\\n11859900,Si,15.6466,0.0,0.0\\n16537400,No,15.6466,0.0571120579565183,0.030578336333865\\n11010400,No,15.6466,0.1357617818231772,0.091585463814462\\n7534000,Si,15.6466,0.1409075536548341,0.0658817937143762\\n9818100,No,15.6466,0.0,0.0\\n9965000,Si,15.6466,0.0,0.0\\n20254600,Si,15.6466,0.3648607143842685,0.148324977324336\\n9989300,No,15.6466,0.0,0.0\\n \\n Output: \\n" ]
{"freq_6": "j5ilz2RtsY4", "freq_4": "NDJjzG/U34g"}
tablejoin
2024-06-24T00:00:00
da9f424fc770103fa6b2639920d84fd8be3c448031ed96d13b975289356f4a67
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: gender,age,profession,occupation,country_of_residence,urban_rural,owns_car,salary,cost_of_living,marital_status\\nFemale,29,Musician,Full-Time,United States,Rural,No,71672,Medium,Single\\nFemale,29,Chef,Full-Time,United States,Rural,No,52829,Medium,Married\\nFemale,40,Architect,Full-Time,United States,Urban,Yes (Loan),62303,High,Single\\nMale,28,Pilot,Full-Time,United States,Urban,Yes (Owned),73258,High,Married\\nFemale,40,Doctor,Full-Time,United States,Rural,No,59573,Medium,Single\\nMale,26,Musician,Full-Time,United States,Urban,No,88218,High,Single\\nMale,29,Marketing Specialist,Full-Time,United States,Urban,Yes (Loan),78838,Medium,Married\\nMale,39,Pilot,Full-Time,United States,Urban,Yes (Loan),74197,High,Single\\nMale,29,Writer,Full-Time,United States,Rural,Yes (Owned),88437,High,Married\\nFemale,38,Pilot,Full-Time,United States,Urban,No,115931,High,Married\\nMale,31,Doctor,Full-Time,United States,Rural,No,111470,High,Single\\nFemale,40,Doctor,Full-Time,United States,Rural,Yes (Loan),103918,High,Single\\nFemale,23,Firefighter,Full-Time,United States,Urban,No,67955,High,Married\\nMale,38,Teacher,Full-Time,United States,Urban,No,84761,Medium,Married\\nFemale,36,Doctor,Full-Time,United States,Rural,No,89057,High,Single\\nFemale,27,Pilot,Full-Time,United States,Rural,Yes (Owned),119808,Medium,Single\\nMale,22,Pilot,Full-Time,United States,Urban,No,112298,Medium,Single\\nMale,23,Marketing Specialist,Full-Time,United States,Urban,Yes (Loan),71946,Medium,Single\\n \\n CSV Table B: 8UKIX1iMOZg,lsTuaMKy100,q9mixw71rsY,NWoi+UEeAUY,Krl1e9fqzyc,LB1c5bVtloU,+3hdejHnpQE,x+dSLMV/+GA\\n2024-04-23T05:00:01.,76515,32,0,Male,6040452,5.0 out of 5 stars,Architect\\n2024-04-23T05:00:01.,99155,28,1,Female,6038888,5.0 out of 5 stars,Architect\\n2024-04-23T05:00:01.,49782,32,2,Male,5941356,5.0 out of 5 stars,Pilot\\n2024-04-23T05:00:01.,116517,33,3,Female,6040452,5.0 out of 5 stars,Pilot\\n2024-04-23T05:00:01.,82120,25,4,Male,5941356,5.0 out of 5 stars,Chef\\n2024-04-23T05:00:01.,89186,32,5,Female,5510456,4.0 out of 5 stars,Pilot\\n2024-04-23T05:00:01.,61713,38,6,Female,6040452,5.0 out of 5 stars,Firefighter\\n2024-04-23T05:00:01.,109924,35,7,Female,5510456,5.0 out of 5 stars,Teacher\\n2024-04-23T05:00:01.,70534,25,8,Male,6038888,5.0 out of 5 stars,Doctor\\n2024-04-23T05:00:01.,71039,28,9,Male,5026787,5.0 out of 5 stars,Firefighter\\n2024-04-23T05:00:01.,103669,39,10,Male,6040452,5.0 out of 5 stars,Writer\\n2024-04-23T05:00:01.,107400,40,11,Female,5510456,5.0 out of 5 stars,Doctor\\n2024-04-23T05:00:01.,42569,33,12,Male,6038888,5.0 out of 5 stars,Marketing Specialist\\n2024-04-23T05:00:01.,57466,27,13,Female,5941356,5.0 out of 5 stars,Teacher\\n2024-04-23T05:00:01.,49245,37,14,Female,5510456,5.0 out of 5 stars,Writer\\n2024-04-23T05:00:01.,111461,34,15,Male,5026787,5.0 out of 5 stars,Chef\\n2024-04-23T05:00:01.,100164,34,16,Female,5510456,5.0 out of 5 stars,Marketing Specialist\\n2024-04-23T05:00:01.,106415,26,17,Female,5026787,5.0 out of 5 stars,Writer\\n2024-04-23T05:00:01.,102207,36,18,Female,5510456,5.0 out of 5 stars,Doctor\\n \\n Output: \\n" ]
{"profession": "x+dSLMV/+GA", "salary": "lsTuaMKy100", "gender": "Krl1e9fqzyc", "age": "q9mixw71rsY"}
tablejoin
2024-06-24T00:00:00
ae4654298c694908b994dd999e784904f1c22e2978e6e958d71cf0e5d5ab5975
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: time,power,temp,humidity,light,CO2,dust\\n2015-08-09 22:38:21,0.55,34,34,0,1963,8.99\\n2015-08-11 13:02:42,0.638,31,36,27,2000,23.53\\n2015-08-31 14:23:02,0.0,35,28,12,2000,1.23\\n2015-08-16 19:11:54,0.066,33,31,0,2000,4.33\\n2015-08-31 07:32:28,-1.0,33,29,0,2000,3.06\\n2015-08-16 09:11:40,0.0,35,31,0,2000,44.52\\n2015-08-27 01:46:24,-1.0,31,31,0,2000,4.9\\n2015-08-16 08:05:55,0.0,34,32,0,2000,33.12\\n2015-08-13 18:28:38,0.528,35,30,27,2000,11.39\\n2015-08-12 04:59:51,-1.0,33,33,0,2000,23.56\\n2015-08-26 14:22:16,-1.0,32,30,35,2000,2.71\\n2015-08-05 08:32:58,0.0,32,40,9,1190,17.35\\n2015-08-17 08:40:28,-1.0,32,32,3,2000,8.11\\n2015-08-12 10:32:45,-1.0,34,33,10,2000,41.84\\n2015-08-30 12:47:11,-1.0,34,29,22,2000,8.04\\n2015-08-15 13:14:12,0.0,35,30,6,2000,22.01\\n \\n CSV Table B: 9etcI5xa42c,JJY6KSu5yhg,zh000AR22V8,sK4/vfuebl0,ws35g9DHMug\\n2024-04-23T05:00:01.,0,2015-08-22 21:49:59,No,0.0\\n2024-04-23T05:00:01.,0,2015-08-31 05:14:27,No,-1.0\\n2024-04-23T05:00:01.,17,2015-08-18 12:38:48,No,-1.0\\n2024-04-23T05:00:01.,0,2015-08-30 06:22:12,No,-1.0\\n2024-04-23T05:00:01.,0,2015-08-31 22:40:53,No,0.572\\n2024-04-23T05:00:01.,0,2015-08-03 04:43:17,Si,0.0\\n2024-04-23T05:00:01.,0,2015-08-12 22:58:13,Si,-1.0\\n2024-04-23T05:00:01.,26,2015-08-25 07:49:46,Si,-1.0\\n2024-04-23T05:00:01.,14,2015-08-17 13:14:00,No,0.528\\n2024-04-23T05:00:01.,0,2015-08-02 06:52:53,No,0.0\\n2024-04-23T05:00:01.,2,2015-08-08 08:37:11,Si,0.0\\n2024-04-23T05:00:01.,0,2015-08-22 21:56:01,No,0.0\\n2024-04-23T05:00:01.,0,2015-08-22 04:23:01,Si,-1.0\\n2024-04-23T05:00:01.,0,2015-08-09 22:00:43,Si,0.0\\n2024-04-23T05:00:01.,12,2015-08-03 17:18:37,No,0.638\\n2024-04-23T05:00:01.,35,2015-08-14 21:37:41,No,0.0\\n2024-04-23T05:00:01.,13,2015-08-31 10:45:43,No,-1.0\\n \\n Output: \\n" ]
{"time": "zh000AR22V8", "light": "JJY6KSu5yhg", "power": "ws35g9DHMug"}
tablejoin
2024-06-24T00:00:00
587e13e04d18246f787cc8d41da67701eb1343795150a63b1996c5ec8270b20e
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: cleanup_site_name,location,zipcode,city,responsible_section,:@computed_region_fny7_vc3j,:@computed_region_x4ys_rtnd,region,latitude,cleanup_site_id\\nBland Property,{'latitude': '45.728,98685,VANCOUVER,Southwest,3,2977.0,Southwest,45.72869,14645\\nCOUNTRY STORE MINI M,{'latitude': '47.598,98826-1455,LEAVENWORTH,Central,8,2956.0,Central,47.598419,6698\\nL & L Exxon,{'latitude': '46.274,99352,RICHLAND,Central,4,2955.0,Central,46.27471,7128\\nBURKS BROS CONOCO,{'latitude': '46.207,99336-3931,KENNEWICK,Central,4,2955.0,Central,46.2078,8264\\nHEISSON STORE,{'latitude': '45.824,98622,HEISSON,Southwest,3,2977.0,Southwest,45.82483,8814\\nKAMAN BEARING & SUPP,{'latitude': '46.969,98520,ABERDEEN,Southwest,6,2983.0,Southwest,46.96953,8704\\nLUCKYS SERVICE,{'latitude': '47.684,98822,ENTIAT,Central,8,2956.0,Central,47.684441,9917\\nPacific Pride Tanker,{'latitude': '47.483,98836,MONITOR,Central,8,2956.0,Central,47.483057,4757\\nWolfkill Feed and Fe,{'latitude': '46.893,99357,ROYAL CITY,Eastern,4,2982.0,Eastern,46.893581,4587\\nUS DOE 200-WA-1,{'latitude': '46.556,99352,RICHLAND,Nuclear Waste Prgm,4,2955.0,Central,46.5562,11562\\nA G EDWARDS INC,{'latitude': '46.151,99336,KENNEWICK,Central,4,2955.0,Central,46.151438,10122\\nUS DOE 100-KR-1,{'latitude': '46.656,99352,RICHLAND,Nuclear Waste Prgm,4,2955.0,Central,46.656433,3975\\nSHOTWELL INDUSTRIES,{'latitude': '48.017,98362,PORT ANGELES,Southwest,6,2976.0,Southwest,48.017589,9260\\nMoore Wrecking Yard,{'latitude': '45.879,98675,YACOLT,Southwest,3,2977.0,Southwest,45.87945,14639\\nElectro Tech Metal F,{'latitude': '45.673,98682,VANCOUVER,Southwest,3,2977.0,Southwest,45.673507,4351\\nSCHMELZER WELL SITE,{'latitude': '46.190,99336,KENNEWICK,Central,4,2955.0,Central,46.190922,3102\\nJR Simplot Co Othell,{'latitude': '46.838,99344,OTHELLO,Eastern,4,2953.0,Eastern,46.838177,2350\\n \\n CSV Table B: +TcFRhetc3o,93uWjlrnDi8,IBOO7n66j2I,0tAjwzEbXgc,zSt62OHmjJ8,9etcI5xa42c,xEEeWKcl26k,O82C1HeOr40\\n6040452,4747,Weak,ANATONE,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '46.133\\n6038888,1504,Weak,CLARKSTON,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '46.402\\n5941356,6157,Weak,PORT ANGELES,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '48.104\\n6040452,10905,New,RICHLAND,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '46.253\\n5941356,2762,Weak,YACOLT,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '45.731\\n5510456,11504,New,WENATCHEE,4.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '47.480\\n6040452,8329,New,ELMA,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '47.004\\n5510456,12622,New,FORKS,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '47.949\\n6038888,3877,Weak,RICHLAND,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '46.695\\n5026787,4273,New,PORT ANGELES,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '48.105\\n6040452,3572,New,SEQUIM,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '48.092\\n5510456,9612,Weak,LEAVENWORTH,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '47.556\\n6038888,2872,Weak,MOSES LAKE,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '47.187\\n5941356,10466,Good,KENNEWICK,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '46.187\\n5510456,7992,New,PORT ANGELES,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '48.116\\n5026787,8293,Weak,PROSSER,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '46.382\\n5510456,8437,New,WENATCHEE,5.0 out of 5 stars,2024-04-23T05:00:01.,0,{'latitude': '47.416\\n \\n Output: \\n" ]
{"city": "0tAjwzEbXgc", "cleanup_site_id": "93uWjlrnDi8", "location": "O82C1HeOr40"}
tablejoin
2024-06-24T00:00:00
bd4b2031ad50538f365ac3312534d813fb7326fd90cf5056ac80b31d189cbb15
data_analysis
[ "Please create a valid join mapping between CSV Table A and CSV Table B. Each column in A maps to 0 or 1 columns in B. Return your response as a Python dictionary, formatted as {col_name_in_df_a : col_name_in_df_b}. Please return only the dictionary. \\n CSV Table A: center,center_search_status,facility,occupied,record_date,last_update,country,contact,phone,location\\nMarshall Space Fligh,Public,ET Flight Environmen,1962-01-01T00:00:00.,1996-03-01T00:00:00.,2015-02-26T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\nKennedy Space Center,Public,Airlock/M7-360/SSPF ,1995-01-01T00:00:00.,1996-03-01T00:00:00.,2015-06-22T00:00:00.,US,Sheryl Chaffee,321-867-8047,{'latitude': '28.538\\nKennedy Space Center,Public,Payload Shipping Con,1986-01-01T00:00:00.,1996-03-01T00:00:00.,2015-06-22T00:00:00.,US,Sheryl Chaffee,321-867-8047,{'latitude': '28.538\\nKennedy Space Center,Public,High Bay 4 Cell/K6-8,1966-01-01T00:00:00.,1996-03-01T00:00:00.,2015-06-22T00:00:00.,US,Sheryl Chaffee,321-867-8047,{'latitude': '28.538\\nMarshall Space Fligh,Public,EH SRB-TPS (Thermal ,1956-01-01T00:00:00.,1996-03-01T00:00:00.,2014-06-02T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\nMarshall Space Fligh,Public,ES Earth Science & A,1991-01-01T00:00:00.,1996-03-01T00:00:00.,2014-03-31T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\nMarshall Space Fligh,Public,EL Ground Control Ex,1958-01-01T00:00:00.,1996-03-01T00:00:00.,2014-06-02T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\nAmes Research Center,Public,N229 - EXPER. AEROTH,1961-01-01T00:00:00.,1996-03-01T00:00:00.,2014-06-13T00:00:00.,US,Rocci Caringello,650 603-9506,{'latitude': '37.414\\nMarshall Space Fligh,Public,ES Low Energy Ion Fa,1974-01-01T00:00:00.,1996-03-01T00:00:00.,2014-03-31T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\nJohnson Space Center,Public,Vibration Acoustic T,,2012-09-26T00:00:00.,2012-09-26T00:00:00.,US,Charles Noel,281.483.3219,{'latitude': '29.559\\nJet Propulsion Lab,Public,DSS 43 Antenna,1963-01-01T00:00:00.,1996-03-01T00:00:00.,2013-08-07T00:00:00.,US,Gary Gray,818.354.0701,{'latitude': '34.178\\nMarshall Space Fligh,Public,EI Manned Habitat EC,1985-01-01T00:00:00.,1996-05-17T00:00:00.,2014-06-02T00:00:00.,US,Pam Caruso,256-544-7795,{'latitude': '34.729\\nKennedy Space Center,Public,Engineering Developm,1966-01-01T00:00:00.,1996-03-01T00:00:00.,2015-06-22T00:00:00.,US,Sheryl Chaffee,321-867-8047,{'latitude': '28.538\\nStennis Space Center,Public,Sensor Laboratory #1,1966-01-01T00:00:00.,1996-03-01T00:00:00.,2015-04-06T00:00:00.,US,Robert Bruce,228-688-1646,{'latitude': '30.385\\n \\n CSV Table B: k1vXu+r6Ouc,GDenm4WiBpQ,pmjzbvItDZo,Bezp8Kegeiw,pg09D/VHAjI,+xkGOBJYDCk,BkPad8F1Zfw\\ngas,Langley Research Cen,1946-01-01T00:00:00.,24591000,1996-03-01T00:00:00.,{'latitude': '37.086,Weak\\ngas,Wallops Flight Facil,1994-01-01T00:00:00.,8334800,1996-03-01T00:00:00.,{'latitude': '37.911,Weak\\ngas,Kennedy Space Center,1966-01-01T00:00:00.,9875400,1996-03-01T00:00:00.,{'latitude': '28.538,Weak\\ngas,Kennedy Space Center,1962-01-01T00:00:00.,8338300,1996-03-01T00:00:00.,{'latitude': '28.538,New\\ngas,Jet Propulsion Lab,1963-01-01T00:00:00.,8995500,1996-03-01T00:00:00.,{'latitude': '34.178,Weak\\ngas,Armstrong Flight Res,,8564500,2010-04-13T00:00:00.,{'latitude': '35.000,New\\ngas,Goddard Space Flight,,8948500,1996-03-01T00:00:00.,{'latitude': '38.995,New\\ngas,NASA Aircraft Manage,,11859900,2009-11-04T00:00:00.,{'latitude': '38.883,New\\ngas,Marshall Space Fligh,1995-01-01T00:00:00.,16537400,1996-03-01T00:00:00.,{'latitude': '34.729,Weak\\ngas,Wallops Flight Facil,1959-01-01T00:00:00.,11010400,1996-03-01T00:00:00.,{'latitude': '37.911,New\\ngas,Glenn Research Cente,1993-01-01T00:00:00.,7534000,1996-03-01T00:00:00.,{'latitude': '41.430,New\\ngas,Jet Propulsion Lab,1992-01-01T00:00:00.,9818100,1996-03-01T00:00:00.,{'latitude': '34.178,Weak\\ngas,Marshall Space Fligh,1965-01-01T00:00:00.,9965000,1996-03-01T00:00:00.,{'latitude': '34.729,Weak\\ngas,Goddard Space Flight,1966-01-01T00:00:00.,20254600,1996-03-01T00:00:00.,{'latitude': '38.995,Good\\n \\n Output: \\n" ]
{"location": "+xkGOBJYDCk", "center": "GDenm4WiBpQ", "record_date": "pg09D/VHAjI", "occupied": "pmjzbvItDZo"}
tablejoin
2024-06-24T00:00:00