the_information_nexus/projects/ytmusic.md

# YouTube Music Data Analysis

## Setup

```python
from ytmusicapi import YTMusic
import pandas as pd
import matplotlib.pyplot as plt
```

# Initialize YTMusic with OAuth credentials
```python
ytmusic = YTMusic('oauth.json')
```

## Fetch Data

### Liked Songs

```python
liked_songs = ytmusic.get_liked_songs(limit=100)
liked_songs_df = pd.DataFrame(liked_songs['tracks'])
liked_songs_df['artists'] = liked_songs_df['artists'].apply(lambda x: x[0]['name'] if x else None)
liked_songs_df.head()
```

### Playlists

```python
playlists = ytmusic.get_library_playlists(limit=25)
playlists_df = pd.DataFrame(playlists)
playlists_df.head()
```

### History

```python
history = ytmusic.get_history()
history_df = pd.DataFrame(history)
history_df.head()
```

## Data Visualization

### Liked Songs by Artist

```python
liked_songs_df['artists'].value_counts().plot(kind='bar', figsize=(10, 5))
plt.title('Liked Songs by Artist')
plt.xlabel('Artist')
plt.ylabel('Number of Liked Songs')
plt.show()
```

### History by Title

```python
history_df['title'].value_counts().plot(kind='bar', figsize=(10, 5))
plt.title('History by Title')
plt.xlabel('Title')
plt.ylabel('Number of Plays')
plt.show()
```

## Save Data to CSV

```python
liked_songs_df.to_csv('liked_songs.csv', index=False)
playlists_df.to_csv('playlists.csv', index=False)
history_df.to_csv('history.csv', index=False)
```
```

### Full Script Breakdown

1. **Setup:**
   - Import necessary libraries (`ytmusicapi`, `pandas`, `matplotlib`).
   - Initialize the YTMusic API with OAuth credentials.

2. **Fetch Data:**
   - Get the user's liked songs and convert them to a DataFrame.
   - Get the user's playlists and convert them to a DataFrame.
   - Get the user's history and convert it to a DataFrame.

3. **Data Visualization:**
   - Visualize the liked songs by artist using a bar chart.
   - Visualize the history by title using a bar chart.

4. **Save Data to CSV:**
   - Save the processed DataFrames to CSV files for further analysis or backup.

### How to Use This Notebook

1. **Ensure you have the `oauth.json` file in your project directory, which contains your OAuth credentials for the YTMusic API.**
2. **Start Jupyter Notebook:**
   ```bash
   jupyter notebook
   ```
3. **Create a new notebook or open an existing one and copy the above cells into the notebook.**
4. **Run the cells step by step to fetch, analyze, visualize, and save your YouTube Music data.**

This setup will provide you with a comprehensive and interactive data analysis report of your YouTube Music telemetry.

---

### Step 1: Set Up Your Python Virtual Environment

First, ensure you have Python installed on your system. I recommend using Python 3.7 or newer. Here’s how you can set up a virtual environment:

1. **Create a New Directory for Your Project (Optional):**
   ```bash
   mkdir yt-music-project
   cd yt-music-project
   ```

2. **Create a Virtual Environment:**
   ```bash
   python -m venv venv
   ```

3. **Activate the Virtual Environment:**
   - On Windows:
     ```bash
     .\venv\Scripts\activate
     ```
   - On macOS and Linux:
     ```bash
     source venv/bin/activate
     ```

### Step 2: Install Required Packages

1. **Ensure your `requirements.txt` includes `ytmusicapi`:**
   You can create a `requirements.txt` file containing at least:
   ```
   ytmusicapi
   ```
   If you already have a `requirements.txt`, make sure `ytmusicapi` is listed.

2. **Install the Required Packages:**
   ```bash
   pip install -r requirements.txt
   ```

### Step 3: Set Up OAuth Authentication

1. **Run OAuth Setup:**
   While in your activated virtual environment and your project directory:
   ```bash
   ytmusicapi oauth
   ```
   Follow the on-screen instructions:
   - Visit the URL provided in the command output.
   - Log in with your Google account.
   - Authorize the application if prompted.
   - Copy the provided code back into the terminal.

   This will generate an `oauth.json` file in your project directory containing the necessary credentials.

### Step 4: Initialize YTMusic with OAuth Credentials

1. **Create a Python Script:**
   You can create a Python script like `main.py` to start coding with the API:
   ```python
   from ytmusicapi import YTMusic
   ytmusic = YTMusic('oauth.json')
   ```

### Step 5: Test by Creating a Playlist

1. **Write Code to Create a Playlist and Search for Music:**
   Add to your `main.py`:
   ```python
   # Create a new playlist
   playlist_id = ytmusic.create_playlist("My Awesome Playlist", "A description of my playlist.")

   # Search for a song
   search_results = ytmusic.search("Oasis Wonderwall")

   # Add the first search result to the new playlist
   if search_results:
       ytmusic.add_playlist_items(playlist_id, [search_results[0]['videoId']])
   ```

2. **Run Your Script:**
   ```bash
   python main.py
   ```

This setup gives you a complete environment to work with the YTMusic API securely and manage your YouTube music data programmatically. You can extend this setup by adding more features, such as handling errors, enhancing functionality, or integrating with other data sources and tools for analysis or backup.