import os import numpy as np import gradio as gr import pandas as pd from zipfile import ZipFile def zip_two_files(data1, data2): with ZipFile('my_csvs.zip', 'w') as csv_zip: csv_zip.writestr("primary_data.csv", data1.to_csv(index=False)) csv_zip.writestr("secondary_data.csv", data2.to_csv(index=False)) return 'my_csvs.zip' def get_split(csv_file,target_columns,primary_cols,combination_of ): df = pd.read_csv(csv_file.name, delimiter=",") target_columns = [target_columns] primary_cols = primary_cols.split(',') + target_columns combination_of = combination_of.split(',') secondary_cols = list(set(df.columns.tolist()) - set(primary_cols)) df["Comb"] = ( df[combination_of] .astype(str) .agg(lambda x: ",".join(x.values), axis=1) .T ) secondary_df = pd.DataFrame({'Id_Apres': range(1, len(df['Comb'].unique())+1), 'Comb': df['Comb'].unique()}) secondary_df = secondary_df.merge(df[['Comb']+secondary_cols], on=['Comb']).drop_duplicates(subset=['Comb']).drop(columns=['Comb']) secondary_df = secondary_df.reset_index(drop=True) primary_df = df.merge(secondary_df, on=combination_of).drop(columns=combination_of) primary_df = primary_df[primary_cols+['Id_Apres']] primary_df = primary_df.reset_index() return zip_two_files(primary_df,secondary_df) iface = gr.Interface(fn = get_split, inputs = [ gr.inputs.File(label='CSV file') , gr.inputs.Textbox(label='Target Column') , gr.inputs.Textbox(label='Primary Column') , gr.inputs.Textbox(label='Combination of Column') ], outputs = [ #gr.outputs.Dataframe(label='Primary data'), #gr.outputs.Dataframe(label='Secondary data'), 'file' ], title = 'Data Splitter ', description="Split your data into 2 parts. Apres.io © 2022 All rights reserved.") iface.launch( debug=True)