https://github.com/roneylaurent/youtube-analytics
YouTube Analytics
https://github.com/roneylaurent/youtube-analytics
creator-economy influencers youtube youtube-analytics youtube-api youtube-channel
Last synced: about 1 month ago
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YouTube Analytics
- Host: GitHub
- URL: https://github.com/roneylaurent/youtube-analytics
- Owner: roneylaurent
- Created: 2024-05-28T20:00:40.000Z (11 months ago)
- Default Branch: master
- Last Pushed: 2024-05-28T20:44:19.000Z (11 months ago)
- Last Synced: 2025-02-01T22:14:41.541Z (3 months ago)
- Topics: creator-economy, influencers, youtube, youtube-analytics, youtube-api, youtube-channel
- Language: Python
- Homepage:
- Size: 4.88 KB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 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:
```bash
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
```python
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
```python
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
```python
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
```python
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
```python
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
```python
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:
```bash
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.