44 lines
2.5 KiB
Python
44 lines
2.5 KiB
Python
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import pandas as pd
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import os
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import numpy as np
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curdir = os.getcwd()
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path_delim = '/'
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# df1 = pd.read_excel(curdir + path_delim + "data/users_sept14_sept19.xlsx", sheet_name="data")
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# df2 = pd.read_excel(curdir + path_delim + "data/20th Sep-Results.xlsx", sheet_name="op")
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df3 = pd.read_excel(curdir + path_delim + "data/21092023-July_Sept.xlsx", sheet_name="op")
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df_final = df3
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# # df = df1.merge(df3, on="_id", how='outer')
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# print(df.columns)
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# # df = pd.concat([df1, df3], ignore_index=True)
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# df['Age'] = 2023 - df['birthYear']
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# df = df[["_id", "name", "abhaId", "aadharId", "Age", "gender", "category", "maritalStatus", "house", "district", "state", "pinCode", "phoneNumber", "classification-Estimated Denovix", "bloodGroup", "createdAt", "caste"]]
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# # print(df.columns)
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# df.rename(columns={'_id': "Sample ID", "name": "Name", "abhaId": "ABHA ID", "aadharId": "Aadhaar ID", "gender": "Gender", "category": "Category", "maritalStatus": "Marital Status", "house": "Address", "district": "District", "state": "State", "pinCode": "Pincode", "phoneNumber": "Mobile Number", "createdAt": "Date", "classification-Estimated Denovix": "Test Result", "bloodGroup": "Blood Group", "Age": "Age", "caste": "Caste"}, inplace = True)
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# df = df.reindex(["Sample ID", "Name", "ABHA ID", "Aadhaar ID", "Age", "Gender", "Caste", "Category", "Marital Status", "Address", "District", "State", "Pincode", "Mobile Number", "Date", "Test Result", "Blood Group"], axis=1)
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# df['Date'] = pd.to_datetime(df["Date"].dt.strftime('%d-%m-%Y'))
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# df = df.sort_values(by=['Date'], ascending=True)
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# df.loc[df['Test Result'] == np.nan, 'Test Result'] = 'Retest'
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# # df.loc[df['Test Result'] == "Inconclusive", 'Test Result'] = 'Retest'
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df_final.loc[df_final['Test Result'] == 'Normal', 'Test Result'] = 'Normal (HbA)'
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df_final.loc[df_final['Test Result'] == 'Sickle Cell Trait', 'Test Result'] = 'Sickle Cell Trait (HbAS)'
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df_final.loc[df_final['Test Result'] == 'SCT', 'Test Result'] = 'Sickle Cell Trait (HbAS)'
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df_final.loc[df_final['Test Result'] == 'SCD', 'Test Result'] = 'Sickle cell Disease (HbSS)'
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df_final.loc[df_final['Test Result'] == 'PBL', 'Test Result'] = 'Positive Borderline'
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df_final.loc[df_final['Test Result'] == 'NBL', 'Test Result'] = 'Negative Borderline'
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df_final.loc[df_final['Gender'] == 'Male', 'Gender'] = 'MALE'
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df_final.loc[df_final['Gender'] == 'Female', 'Gender'] = 'FEMALE'
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print(df_final.groupby(["Test Result"]).describe())
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writer = pd.ExcelWriter(curdir + path_delim + "data/July_Sept9.xlsx", engine = 'openpyxl')
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df_final.to_excel(writer, sheet_name = 'op', index=False)
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writer.close()
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