https://github.com/caesaredia/ymusic-project
Exploratory data analysis (EDA) of music streaming behavior in two fictional cities using Python, Pandas, and Jupyter Notebook. It explores user behavior, genre preferences, and listening patterns throughout the week.
https://github.com/caesaredia/ymusic-project
data-analysis eda pandas python
Last synced: about 2 months ago
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Exploratory data analysis (EDA) of music streaming behavior in two fictional cities using Python, Pandas, and Jupyter Notebook. It explores user behavior, genre preferences, and listening patterns throughout the week.
- Host: GitHub
- URL: https://github.com/caesaredia/ymusic-project
- Owner: caesaredia
- Created: 2025-04-09T05:04:53.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-10T07:36:45.000Z (about 1 year ago)
- Last Synced: 2025-05-07T20:18:12.026Z (about 1 year ago)
- Topics: data-analysis, eda, pandas, python
- Language: Jupyter Notebook
- Homepage:
- Size: 2.11 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Music Streaming Behavior in Springfield & Shelbyville 🎧
This project analyzes music streaming activity in two fictional cities, Springfield and Shelbyville. Using Python and Jupyter Notebook, it explores user behavior, genre preferences, and listening patterns throughout the week.
## Objectives
- Analyze music listening patterns in two cities
- Identify peak streaming times and most popular genres
- Understand day-wise and city-wise streaming behavior
## Key Insights (in the notebook)
- Streaming peaks in the **evenings**
- Both cities show high interest in **pop** and **hip-hop**
- Listening behavior differs slightly by day between Springfield and Shelbyville
## Notebook
* [`ymusic_analysis.ipynb`](./ymusic_analysis.ipynb): Exploratory data analysis of music listening behavior.
## Tools Used
- **Python**
- **Pandas**
- **Matplotlib** & **Seaborn**
- **Jupyter Notebook**
## Dataset
The dataset is stored in [`data/ymusic_data.csv`](./data/ymusic_data.csv), containing anonymized records of music listening behavior from various urban areas.
- Columns include:
- `userID`: Unique user identifier
- `City`: Either "Springfield" or "Shelbyville"
- `Track`: Song title
- `artist`: Artist name
- `genre`: Music genre
- `time`: Time of streaming
- `Day`: Day of the week
## Author
Nabilla Hafsah Caesaredia
## How to Run
Clone the repo and run the notebook:
```bash
git clone https://github.com/caesaredia/ymusic_project.git
cd ymusic_project
jupyter notebook music_streaming_analysis.ipynb