CSV Files clear extra rows, merge 2 files, and add gap number, youtube scrape

 import pandas as pd

def synchronize_csv_files(old_csv_path, new_csv_path, output_csv_path):

# Read the old and new CSV files into DataFrames

old_df = pd.read_csv(old_csv_path)

new_df = pd.read_csv(new_csv_path)

# Find the matching value in the first column of the second row in the new CSV

matching_value = old_df.iloc[1, 0]

# Delete rows from the new CSV until the matching value is found in the first column

while new_df.iloc[1, 0] != matching_value:

new_df = new_df.iloc[1:]

# Reset the index of the new DataFrame

new_df.reset_index(drop=True, inplace=True)

# Combine the rows from both CSV files into a single DataFrame

combined_df = pd.concat([old_df, new_df], axis=1)

# Save the synchronized CSV to the output file

combined_df.to_csv(output_csv_path, index=False)

def calculate_numbers(input_csv_path, output_csv_path):

# Read the synchronized CSV file into a DataFrame

df = pd.read_csv(input_csv_path)

# Calculate the result in the 6th column based on the values in the 2nd and 5th columns

df['GAP'] = df['Views.1'] - df['Views']

# Save the modified CSV to the output file with a new name

df.to_csv(output_csv_path, index=False)

# Example usage:

old_csv_path = "/Users/jitendersingh/Downloads/Smart Enough 2 nov.csv"

new_csv_path = "/Users/jitendersingh/Downloads/Smart Enough 3 nov.csv"

output_csv_path = "/Users/jitendersingh/Downloads/temp_csv.csv"

synchronize_csv_files(old_csv_path, new_csv_path, output_csv_path)

# Example usage:

input_csv_path = "/Users/jitendersingh/Downloads/temp_csv.csv"

output_csv_path = "/Users/jitendersingh/Downloads/synchronized_csv_with_numbers.csv"

calculate_numbers(input_csv_path, output_csv_path)