ActiveSubstance_Tagging.py

import openpyxl
import numpy as np
import datetime
import pandas as pd
import os
import glob


##                                                                                  Import  files from a folder:


# Ask the user for the location path of the files.

def Read_multipleFiles ():


    file_path = input('Enter a file path: ')
    file_type = input('Define a file type (Excel, csv): ')


    # Use os to get all the  files in the folder

    if file_type.lower() == "excel":

        if os.path.exists(file_path):


            files_xlsx = glob.glob(os.path.join(file_path, "*.xlsx"))

            df = []

            # Loop over list of files to append to empty dataframe:

            df = pd.concat((pd.read_excel(f) for f in files_xlsx), ignore_index=True)

            df.fillna('EMPTY', inplace=True)


            #Erase duplicates in the dataframe.

            Datos = df.drop_duplicates(keep="first")

            Dup = len(df) - len(Datos)

            print(Dup,"duplicates removed")


            if len(files_xlsx) == 1:

                print("There is", len(files_xlsx),"file in the folder")

            else:

                print("There are", len(files_xlsx),"files in the folder")

        else:
            print('The specified file path does NOT exist')

        print(files_xlsx)

    
    elif file_type.lower == "csv":
        
        
        if os.path.exists(file_path):

            files_csv = glob.glob(os.path.join(file_path, "*.csv"))


            df = []


            # Loop over list of files to append to empty dataframe:

            df = pd.concat((pd.read_csv(f,sheet_name= "Results") for f in files_csv), ignore_index=True)

            df.fillna('EMPTY', inplace=True)


            #Erase duplicates in the dataframe.

            Datos = df.drop_duplicates(keep="first")

            Dup = len(df) - len(Datos)

            print(Dup,"duplicates removed")

            if len(files_csv) == 1:

                print("There is", len(files_csv),"file in the folder")

            else:

                print("There are", len(files_csv),"files in the folder")

        else:
            print('The specified file path does NOT exist')

        print(files_csv)
    

Read_multipleFiles()





def Cortellis_ATCtagging(Datos):

    file_path = input("Enter a file path to export your results: ")

    # Iteration through each row on the dataframe and appending to each list the right tag for "Type of active substance" and "Category" for each drug.

    Datos["concat"] = Datos["Technologies"] + "; " + Datos["Other Actions"]

    Type = []
    Category =[]

    # For loop to iterate through the columns of interest in the data frame

    for colums,rows in Datos.iterrows():

        if "small molecule therapeutic" in str(rows["concat"]).lower() or  "small molecule therapeutic" in str(rows["Extract"]).lower():

            Type.append("Small molecule therapeutic") 
            Category.append("Other")
    
        elif "vaccine" in str(rows["concat"]).lower() or "vaccine" in str(rows["Extract"]).lower():
                
            Type.append("Biological therapeutic") 
            Category.append("Vaccine")

        elif "gene therapy" in str(rows["concat"]).lower() or "gene therapy" in str(rows["Extract"]).lower() or "gene editing" in str(rows["concat"]).lower() or "gene editing" in str(rows["Extract"]).lower() or "gene technology" in str(rows["concat"]).lower(): 
                    
            Type.append("Biological therapeutic") 
            Category.append("Gene Therapy")   
                    
        elif "cell therapy" in str(rows["concat"]).lower() or "cell therapy" in str(rows["Extract"]).lower():

            Type.append("Biological therapeutic") 
            Category.append("Cell Therapy")

        elif "oligo" in str(rows["concat"]).lower() or "RNA" in str(rows["concat"]) or "antisense" in str(rows["concat"]).lower():
                            
            Type.append("Biological therapeutic") 
            Category.append("Oligonucleotide")

        elif "antibody conjugated" in str(rows["concat"]).lower() or "antibody drug conjugate" in str(rows["concat"]).lower() or "conjugated antibody" in str(rows["concat"]).lower() or "antibody conjugated" in str(rows["Extract"]).lower():

            Type.append("Biological therapeutic") 
            Category.append("Antibody-drug conjugated")

        elif "antibody" in str(rows["concat"]).lower():
                                    
            Type.append("Biological therapeutic") 
            Category.append("Antibody")

        elif "protein fusion" in str(rows["concat"]).lower() or "protein recombinant" in str(rows["concat"]).lower()  or "glycoprotein" in str(rows["concat"]).lower() or "protein conjugated" in str(rows["concat"]).lower() or "recombinant enzyme" in str(rows["concat"]).lower()  or "enzyme" in str(rows["concat"]).lower() or "lipoprotein" in str(rows["concat"]).lower():
                                        
            Type.append("Biological therapeutic") 
            Category.append("Therapeutic protein")
                                                    
        elif "peptide" in str(rows["concat"]).lower():
                                            
            Type.append("Biological therapeutic") 
            Category.append("Peptide")
        
        elif "biological therapeutic" in str(rows["Technologies"]).lower() or "virus recombinant" in str(rows["Technologies"]).lower() or "virus therapy" in str(rows["Technologies"]).lower() or "probiotic" in str(rows["Extract"]).lower() or "yeast recombinant" in str(rows["Technologies"]).lower()  or "bacteria recombinant" in str(rows["Technologies"]).lower() :

            Type.append("Biological therapeutic")
            Category.append("Other")
        
        elif "small molecule" in str(rows["Extract"]).lower() :

            Type.append("Small molecule therapeutic") 
            Category.append("Other") 

        else:
            
            Type.append("Other") 
            Category.append("Other")


    #Datos["Type of active substance"] = Type

    Datos.drop(["concat"], axis = 1, inplace = True)

    Datos["Type of active substance"] = Type
    Datos["Category"] = Category

    Datos.replace('EMPTY',"", inplace=True)

    ##                                                                                 Exporting dataframe in an excel file:


    # Export the dataframe in an excel file at the same location path where we got the files.

    Datos.to_excel(file_path + "\2023_Cortellis_tagging_Final.xlsx", index= False) 
    

Cortellis_ATCtagging()