https://github.com/asma-hachaichi/data-explorer
This Streamlit app enables users to upload a CSV file, navigate through different pages for data analysis including data description, feature analysis, and data statistics.
https://github.com/asma-hachaichi/data-explorer
analysis data-science streamlit
Last synced: 3 months ago
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This Streamlit app enables users to upload a CSV file, navigate through different pages for data analysis including data description, feature analysis, and data statistics.
- Host: GitHub
- URL: https://github.com/asma-hachaichi/data-explorer
- Owner: asma-hachaichi
- Created: 2024-02-08T18:25:02.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-02-08T18:33:42.000Z (over 1 year ago)
- Last Synced: 2025-02-06T09:36:08.082Z (4 months ago)
- Topics: analysis, data-science, streamlit
- Language: Python
- Homepage:
- Size: 1.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Data Explorer
## Description
This Streamlit application offers a comprehensive data analysis platform, allowing users to upload CSV files and explore their data through various lenses. It facilitates an understanding of the dataset by providing descriptive statistics, feature analysis, and visual insights.
## Features
- **CSV File Upload**: Users can upload their dataset in CSV format.
- **Data Description**: Displays basic descriptive statistics and the initial rows of the dataset.
- **Feature Analysis**: Identifies numerical and categorical columns, and reports on missing values.
- **Data Statistics**: Generates histograms for numerical features and bar charts for categorical features, aiding in the visual analysis of the dataset.
## How to Run
To run this application, follow these steps:
1. Ensure you have Streamlit and other required libraries (Pandas, Seaborn, Matplotlib) installed.
2. Save the provided script to a file, for example, `app.py`.
3. Open your terminal or command prompt.
4. Navigate to the directory containing `app.py`.
5. Run the app with Streamlit by typing:
`` streamlit run app.py ``
## Requirements
- Python
- Streamlit
- Pandas
- Seaborn
- Matplotlib
## License
This project is licensed under the MIT License. See the LICENSE file for more details.