Python program to convert arrays to individual values

1. Install Python: If you haven't already, download and install the latest version of Python from the official website: https://www.python.org/downloads/

2. Install pandas: Open a terminal (Command Prompt on Windows or Terminal on macOS/Linux) and run the following command to install the pandas library, which the script depends on:

   pip install pandas
   

3. Save the script: Copy the provided Python script and save it as a .py file, for example, ConvertArray2MultipleRows.py

4. Prepare the input CSV file: Make sure your input CSV file is formatted correctly, with array values enclosed in double quotes. For example:

   name,age,colors
   John,25,"[red,blue,green]"
   Sarah,30,"[yellow,purple]"
   

   Save the CSV file, for example, as input.csv.

5. Run the script: In the terminal, navigate to the folder where you saved the ConvertArray2MultipleRows.py script using the cd command. For example:

   cd path/to/your/script/folder
   

   Replace path/to/your/script/folder with the actual path to the folder containing the script.

6. Execute the script by running the following command in the terminal:

   python ConvertArray2MultipleRows.py
   

7. Provide the input and output file paths: The script will prompt you to enter the input CSV file path and the output CSV file path. Enter the paths and press Enter. For example:

   Please enter input CSV file name(along with path): input.csv

   Replace input.csv with the actual file paths if they are located in different folders.

8. Then the program starts conversion and displays the number of arrays converted as

   Total number of Arrays found and Converted =  49841

9. Finally enter the Output file name where it has to be stored when prompted

   Please enter the output CSV file name: Output.csv

10. Check the output: The script will process the input CSV file and create a new output CSV file with the specified file path. Open the output CSV file to verify the result.

Python Code (ConvertArray2MultipleRows.py)

import ast
import pandas as pd
import re

# Global counter to know how many arrays are present
v_occurances = 0

#To check if a entry is an array
def is_array(value):
    return isinstance(value, (list, tuple)) or re.match(r'\[.*\]', str(value))

#Which columns are having arrays as values
def find_array_columns(df):
    array_columns = []
    for column in df.columns:
        if df[column].apply(is_array).any():
            array_columns.append(column)
    return array_columns

#Converting arrays to list
def convert_to_list(value):
    global v_occurances
    if is_array(value) and re.search(r'\[.*?,.*?\]',str(value)):
        v_occurances = v_occurances + 1
        ret = ast.literal_eval(value)
        return ret
    return [value]

#Splitting the arrays
def split_rows_by_array(df, array_columns):
    for column in array_columns:
        df[column] = df[column].apply(convert_to_list)
        df = df.explode(column).reset_index(drop=True)
    return df

def main():
    # Get the input CSV file path from the user
    file_path = input("Please enter input CSV file name(along with path): ")
    # Read the CSV file
    df = pd.read_csv(file_path,low_memory=False)
    # Find columns containing array values
    array_columns = find_array_columns(df)
    # Split the rows based on the array values in the identified columns
    new_df = split_rows_by_array(df, array_columns)
    print('Total number of Arrays Found and Converted = ',v_occurances)
    # Get the output CSV file path from the user
    output_file_path = input("Please enter the output CSV file name: ")

    # Save the resulting dataframe to the specified output CSV file
    new_df.to_csv(output_file_path, index=False)

if __name__ == '__main__':
    main()