popular_vids.py

import pandas as pd
import numpy as np
import yaml

# Got to YouTube Studio -> Analytics and export the default view for Lifetime

def process_most_popular():
    """ Process the most popular videos """

    # Read in the data
    videos = pd.read_csv('Table data.csv')

    videos = videos.drop([0])
    videos = videos.drop(['Impressions',
                        'Impressions click-through rate (%)',
                        'Impressions',
                        # 'Average view duration',
                        'Estimated revenue (GBP)',
                        'Video publish time',
                        'Subscribers',
                        'Watch time (hours)',
                        ], axis=1)
    videos = videos[videos['Views'].notna()]
    videos['Views'] = videos['Views'].astype(int)

    videos['title'] = videos['Video title']

    # Calculate the 90th percentile of views
    percentile_90 = videos['Views'].quantile(0.9)

    # Add a new column for the top 10% flag
    videos['popular'] = videos['Views'].apply(lambda x: 'True' if x >= percentile_90 else 'False')

    videos['Content'] = videos['Content'].str.strip()

    videos['Views_str'] = pd.to_numeric(videos['Views'], errors='coerce').fillna(0).astype(int)
    videos['Views_str'] = videos['Views'].apply(lambda x: "{:,}".format(x))

    # Manually construct the YAML string
    yaml_string = "\n".join(
        '- Content: "{}"\n  Views: {}\n  popular: {}\n  title: "{}"\n  views_str: "{}"'.format(row['Content'], row['Views'], row['popular'], row['title'], row['Views_str']) 
        for index, row in videos.iterrows()
    )

    # Write to a YAML file
    with open('web/_data/popular_videos.yaml', 'w') as file:
        file.write(yaml_string)

def process_best_watchtime():
    # Read in the data
    videos = pd.read_csv('Table data.csv')

process_most_popular()
process_best_watchtime()