A converting python script that converts a CSV file produced from RaceChrono Pro format to general Telemetry Overlay format. Created with ChatGPT: https://chat.openai.com/share/7c8e8f2c-60ee-4024-86cd-bc82a3b3c06c

csv_converter_from_race_chrono_pro_to_telemetry_overlay.py

import pandas as pd
import argparse

def process_file(input_file_path, output_file_path):
    # Read the file line by line until we find the header row starting with 'timestamp'
    with open(input_file_path, 'r') as file:
        lines = file.readlines()

    # Get the line number where 'timestamp' is found
    line_number = next(i for i, line in enumerate(lines) if line.lower().startswith('timestamp'))

    # Get the title row as a list of strings
    title_row = lines[line_number].strip().split(',')

    # Load the CSV file again, skipping the rows up to the title row, and also skip the subsequent 2 rows (for units and source)
    df = pd.read_csv(input_file_path, skiprows=range(line_number + 3), header=None)

    # Assign the correct column names
    df.columns = title_row

    # Drop duplicate columns, keeping only the last occurrence
    df = df.loc[:, ~df.columns.duplicated(keep='last')]

    # Create 'utc (ms)' column by multiplying 'timestamp' by 1000 and converting to integer
    df['utc (ms)'] = (df['timestamp'] * 1000).astype(int)

    # Rename the specified columns
    df.rename(columns={
        'altitude': 'alt (m)', 
        'latitude': 'lat (deg)', 
        'longitude': 'lon (deg)', 
        'rpm': 'engine (rpm)'
    }, inplace=True)

    # Save the updated DataFrame to a new CSV file
    df.to_csv(output_file_path, index=False)

    print(f"Processed file saved to: {output_file_path}")

def main():
    parser = argparse.ArgumentParser(description='Process CSV data file.')
    parser.add_argument('-i', '--input', required=True, help='Input CSV file path')
    parser.add_argument('-o', '--output', required=True, help='Output CSV file path')

    args = parser.parse_args()

    process_file(args.input, args.output)

if __name__ == "__main__":
    main()