Datasets:
1T Conte
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Parent(s):
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fix: metadata
Browse files- README.md +6 -7
- amazon_reviews_2013/test-0000-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0001-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0002-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0003-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0004-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0005-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0006-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0007-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0008-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0009-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0010-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0011-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0012-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0013-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0014-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0015-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0016-of-0018.parquet +2 -2
- amazon_reviews_2013/test-0017-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0000-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0001-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0002-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0003-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0004-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0005-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0006-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0007-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0008-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0009-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0010-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0011-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0012-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0013-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0014-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0015-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0016-of-0018.parquet +2 -2
- amazon_reviews_2013/train-0017-of-0018.parquet +2 -2
- convert.py +14 -6
README.md
CHANGED
@@ -7,7 +7,7 @@ dataset_info:
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- name: product/title
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dtype: string
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- name: product/price
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dtype:
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- name: review/helpfulness
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dtype: string
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- name: review/helpfulness_ratio
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@@ -18,12 +18,11 @@ dataset_info:
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dtype:
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class_label:
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names:
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'0':
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'1':
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'2':
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- name: review/time
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dtype: int64
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- name: review/summary
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- name: product/title
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dtype:
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'0': 1 star
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1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f47c16435c22e438809f18073c5277309b0bd529c4f3ed81aaf573187516da5c
|
3 |
+
size 847809703
|
amazon_reviews_2013/train-0016-of-0018.parquet
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5a7b4a0743dcb96177024da469d0ee14edaf3ac00277a279e646de6bdbfcc0b8
|
3 |
+
size 607961510
|
amazon_reviews_2013/train-0017-of-0018.parquet
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e4dc27bbb768e68783b3f00ba04becca47072636106fd0db818683c17f2684d0
|
3 |
+
size 453600036
|
convert.py
CHANGED
@@ -6,7 +6,9 @@ Usage:
|
|
6 |
$ python convert.py
|
7 |
"""
|
8 |
|
|
|
9 |
import os
|
|
|
10 |
import gzip
|
11 |
|
12 |
from glob import glob
|
@@ -51,6 +53,14 @@ CATEGORIES = {
|
|
51 |
"Watches.txt.gz": "Watch", # 68,356 reviews
|
52 |
}
|
53 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
54 |
CATEGORIES_LIST = list(CATEGORIES.values())
|
55 |
|
56 |
|
@@ -89,8 +99,8 @@ def save_parquet(data, chunk):
|
|
89 |
|
90 |
df_train, df_test = train_test_split(df, test_size=TEST_SIZE, random_state=42)
|
91 |
|
92 |
-
df_train.to_parquet(fname_train)
|
93 |
-
df_test.to_parquet(fname_test)
|
94 |
|
95 |
|
96 |
def parse_file(filename):
|
@@ -124,12 +134,10 @@ def clean(entry):
|
|
124 |
|
125 |
if entry["product/price"] == "unknown":
|
126 |
entry["product/price"] = None
|
127 |
-
else:
|
128 |
-
entry["product/price"] = float(entry["product/price"])
|
129 |
|
130 |
-
entry["review/score"] =
|
131 |
entry["review/time"] = int(entry["review/time"])
|
132 |
-
entry["product/category"] = CATEGORIES_LIST.index(entry["product/category"])
|
133 |
|
134 |
numerator, demoninator = entry["review/helpfulness"].split("/")
|
135 |
numerator = int(numerator)
|
|
|
6 |
$ python convert.py
|
7 |
"""
|
8 |
|
9 |
+
import math
|
10 |
import os
|
11 |
+
import sys
|
12 |
import gzip
|
13 |
|
14 |
from glob import glob
|
|
|
53 |
"Watches.txt.gz": "Watch", # 68,356 reviews
|
54 |
}
|
55 |
|
56 |
+
REVIEW_SCORE = {
|
57 |
+
"1.0": 0,
|
58 |
+
"2.0": 1,
|
59 |
+
"3.0": 2,
|
60 |
+
"4.0": 3,
|
61 |
+
"5.0": 4,
|
62 |
+
}
|
63 |
+
|
64 |
CATEGORIES_LIST = list(CATEGORIES.values())
|
65 |
|
66 |
|
|
|
99 |
|
100 |
df_train, df_test = train_test_split(df, test_size=TEST_SIZE, random_state=42)
|
101 |
|
102 |
+
df_train.to_parquet(fname_train, index=False)
|
103 |
+
df_test.to_parquet(fname_test, index=False)
|
104 |
|
105 |
|
106 |
def parse_file(filename):
|
|
|
134 |
|
135 |
if entry["product/price"] == "unknown":
|
136 |
entry["product/price"] = None
|
|
|
|
|
137 |
|
138 |
+
entry["review/score"] = REVIEW_SCORE[entry["review/score"]]
|
139 |
entry["review/time"] = int(entry["review/time"])
|
140 |
+
entry["product/category"] = int(CATEGORIES_LIST.index(entry["product/category"]))
|
141 |
|
142 |
numerator, demoninator = entry["review/helpfulness"].split("/")
|
143 |
numerator = int(numerator)
|