Update app.py

app.py

@@ -1,4 +1,4 @@
-import pandas_profiling as pp
+# import pandas_profiling as pp
 import pandas as pd
 import tensorflow as tf
 
@@ -44,33 +44,6 @@ CHOICES = ["SNOMED", "LOINC", "CQM"]
 JSONOBJ = """{"items":{"item":[{"id": "0001","type": null,"is_good": false,"ppu": 0.55,"batters":{"batter":[{ "id": "1001", "type": "Regular" },{ "id": "1002", "type": "Chocolate" },{ "id": "1003", "type": "Blueberry" },{ "id": "1004", "type": "Devil's Food" }]},"topping":[{ "id": "5001", "type": "None" },{ "id": "5002", "type": "Glazed" },{ "id": "5005", "type": "Sugar" },{ "id": "5007", "type": "Powdered Sugar" },{ "id": "5006", "type": "Chocolate with Sprinkles" },{ "id": "5003", "type": "Chocolate" },{ "id": "5004", "type": "Maple" }]}]}}"""
 
 
-def profile_dataset(dataset=datasetSNOMED, username="awacke1", token=HF_TOKEN, dataset_name="awacke1/SNOMED-CT-Code-Value-Semantic-Set.csv"):
-    df = pd.read_csv(dataset.Description)
-    if len(df.columns) <= 15:
-        profile = pp.ProfileReport(df, title=f"{dataset_name} Report")
-    else:
-        profile = pp.ProfileReport(df, title=f"{dataset_name} Report", minimal = True)
-    
-    repo_url = create_repo(f"{username}/{dataset_name}", repo_type = "space", token = token, space_sdk = "static", private=False)
-    
-    profile.to_file("./index.html")
-
-    upload_file(path_or_fileobj ="./index.html", path_in_repo = "index.html", repo_id =f"{username}/{dataset_name}", repo_type = "space", token=token)
-    readme = f"---\ntitle: {dataset_name}\nemoji: ✨\ncolorFrom: green\ncolorTo: red\nsdk: static\npinned: false\ntags:\n- dataset-report\n---"    
-    with open("README.md", "w+") as f:
-        f.write(readme)
-    upload_file(path_or_fileobj ="./README.md", path_in_repo = "README.md", repo_id =f"{username}/{dataset_name}", repo_type = "space", token=token)
-    return f"Your dataset report will be ready at {repo_url}"
-
-#def lowercase_title(example):
-#    return {"Description": example[title].lower()}
-
-# demonstrate map function of dataset
-#JSONOBJ_MAP=datasetLOINC.map(lowercase_title)
-#JSONOBJ_MAP=datasetLOINC.filter(lambda example: example["Description"].startswith("Mental health")) 
-
-
-
 
 def concatenate_text(examples):
     return {
@@ -180,13 +153,7 @@ def fn(    text1,    text2,    num,    slider1,    slider2,    single_checkbox,
     print(start_with_searchTermLOINC )
     print(start_with_searchTermSNOMED )
     print(start_with_searchTermCQM)
-    
-    #print(start_with_searchTermLOINC["train"][0] )
-    #print(start_with_searchTermSNOMED["train"][0] )
-    #print(start_with_searchTermCQM["train"][0] )
-        
-    #returnMsg=profile_dataset()
-    #print(returnMsg)
+
     
 #    try:
         #top1matchLOINC = json.loads(start_with_searchTermLOINC['train'])