https://github.com/asghar-rizvi/youtube-statistics-project
This project analyzes a dataset of global YouTube statistics to uncover insights about YouTube channels, their ranks, and other attributes. The dataset used for this analysis was obtained from Kaggle.
https://github.com/asghar-rizvi/youtube-statistics-project
data-analysis data-analysis-python data-science data-science-projects matplotlib numpy pandas pycharm-ide python seaborn
Last synced: 2 days ago
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This project analyzes a dataset of global YouTube statistics to uncover insights about YouTube channels, their ranks, and other attributes. The dataset used for this analysis was obtained from Kaggle.
- Host: GitHub
- URL: https://github.com/asghar-rizvi/youtube-statistics-project
- Owner: asghar-rizvi
- Created: 2024-07-30T16:42:48.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-30T16:58:55.000Z (almost 2 years ago)
- Last Synced: 2025-02-26T13:15:57.481Z (over 1 year ago)
- Topics: data-analysis, data-analysis-python, data-science, data-science-projects, matplotlib, numpy, pandas, pycharm-ide, python, seaborn
- Language: Python
- Homepage:
- Size: 858 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# YouTube-Statistics-Project
This project analyzes a dataset of global YouTube statistics to uncover insights about YouTube channels, their ranks, and other attributes. The dataset used for this analysis was obtained from Kaggle.
## Project Structure
├── Data_sets
│ ├── Global YouTube Statistics.csv
│ └── cleaned_data.xlsx
├── main.py
├── Loading_file.py
├── Cleaning_file.py
├── Analysis.py
├── Visuals.py
└── README.md
- **Data_sets/**: Contains the original and cleaned datasets.
- **main.py**: The main script that orchestrates the data loading, cleaning, analysis, and visualization.
- **Loading_file.py**: Script for loading the dataset.
- **Cleaning_file.py**: Script for cleaning the dataset.
- **Analysis.py**: Script for performing various analyses on the dataset.
- **Visuals.py**: Script for generating visualizations from the data.
- **README.md**: This file, describing the project.
## Getting Started
### Prerequisites
To run this project, you will need the following Python libraries:
- pandas
- numpy
- matplotlib
- seaborn
- openpyxl
You can install these libraries using pip:
```bash
pip install pandas numpy matplotlib seaborn openpyxl