YouTube Channel Analysis README

Overview

This script analyzes a YouTube channel by retrieving and analyzing data from the YouTube API. It collects video details such as views, likes, and comments, and saves the analysis in a CSV file. The script is written in Python and uses the googleapiclient and pandas libraries.

Prerequisites

Before you run this script, ensure you have the following installed:

• Python 3.x
• googleapiclient library
• pandas library

You can install the required libraries using pip:

pip install google-api-python-client pandas

Setup

1. API Key: Obtain a YouTube Data API v3 key from the Google Developer Console. Replace 'YOUR-API' with your API key in the script.

2. Channel ID: Identify the YouTube channel ID you wish to analyze. Replace 'THE-CHANNEL-ID' in the script with the channel ID.

Script Explanation

1. Import Libraries

import os
import pandas as pd
from googleapiclient.discovery import build

• os: For interacting with the operating system.
• pandas: For data manipulation and analysis.
• googleapiclient.discovery: For interacting with the YouTube Data API.

2. Configure the YouTube API

API_KEY = 'YOUR-API'
youtube = build('youtube', 'v3', developerKey=API_KEY)

• Replace 'YOUR-API' with your actual YouTube Data API v3 key.

3. Retrieve Channel Videos

def get_channel_videos(channel_id):
    videos = []
    request = youtube.search().list(part='snippet', channelId=channel_id, maxResults=50, order='date')
    response = request.execute()
    
    while response:
        for item in response['items']:
            if item['id']['kind'] == 'youtube#video':
                video_id = item['id']['videoId']
                videos.append(video_id)
        
        if 'nextPageToken' in response:
            request = youtube.search().list(part='snippet', channelId=channel_id, maxResults=50, order='date', pageToken=response['nextPageToken'])
            response = request.execute()
        else:
            break

    return videos

• This function retrieves video IDs from a given channel using the YouTube Data API.

4. Retrieve Video Details

def get_video_details(video_ids):
    video_details = []
    for i in range(0, len(video_ids), 50):
        request = youtube.videos().list(part='snippet,statistics', id=','.join(video_ids[i:i+50]))
        response = request.execute()
        
        for item in response['items']:
            video_data = {
                'video_id': item['id'],
                'title': item['snippet']['title'],
                'views': int(item['statistics'].get('viewCount', 0)),
                'likes': int(item['statistics'].get('likeCount', 0)),
                'comments': int(item['statistics'].get('commentCount', 0))
            }
            video_details.append(video_data)
    
    return video_details

• This function retrieves details such as views, likes, and comments for each video.

5. Analyze Channel Data

def analyze_channel(channel_id):
    video_ids = get_channel_videos(channel_id)
    video_details = get_video_details(video_ids)
    
    df = pd.DataFrame(video_details)
    print(f"Total Videos: {len(df)}")
    print(f"Average Views: {df['views'].mean()}")
    print(f"Average Likes: {df['likes'].mean()}")
    print(f"Average Comments: {df['comments'].mean()}")

    return df

• This function analyzes the collected video data and prints out the total number of videos, average views, likes, and comments.

6. Main Function

if __name__ == "__main__":
    channel_id = 'THE-CHANNEL-ID'
    df = analyze_channel(channel_id)
    df.to_csv('youtube_channel_analysis.csv', index=False)
    print("Data saved to 'youtube_channel_analysis.csv'")

• The main function executes the analysis for a specified channel ID and saves the results to a CSV file.

Running the Script

1. Ensure you have replaced 'YOUR-API' and 'THE-CHANNEL-ID' with your API key and the channel ID you wish to analyze.
2. Run the script:

python your_script_name.py

3. The script will print the analysis results and save them to a file named youtube_channel_analysis.csv.

Output

• The output CSV file will contain columns for video_id, title, views, likes, and comments for each video in the analyzed channel.

By following these steps, you can successfully analyze a YouTube channel's video performance using this script.