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https://github.com/venkat-a/python-eda-exploratory-data-analysis-

This project focuses on conducting exploratory data analysis (EDA) using Python. Utilizing powerful libraries such as Pandas for data manipulation and Plotly for interactive visualization, the project aims to uncover insights from datasets through comprehensive analysis and visualization techniques.
https://github.com/venkat-a/python-eda-exploratory-data-analysis-

descriptive-statistics matplotlib numpy pandas seaborn statistical-analysis visualization

Last synced: about 2 months ago
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This project focuses on conducting exploratory data analysis (EDA) using Python. Utilizing powerful libraries such as Pandas for data manipulation and Plotly for interactive visualization, the project aims to uncover insights from datasets through comprehensive analysis and visualization techniques.

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# Python-EDA-Exploratory-Data-Analysis-
This project focuses on conducting exploratory data analysis (EDA) using Python. Utilizing powerful libraries such as Pandas for data manipulation and Plotly for interactive visualization, the project aims to uncover insights from datasets through comprehensive analysis and visualization techniques.
# Installation

To run this project, you will need Python installed on your system. Clone this repository to your local machine, and navigate to the project directory. Then, install the required dependencies:

bash
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pip install pandas plotly

# Usage

The main Jupyter notebook, Eda_Analysis_Python.ipynb, contains the analysis. You can run it using Jupyter Lab or Jupyter Notebook by executing:

bash
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jupyter lab Eda_Analysis_Python.ipynb
# or
jupyter notebook Eda_Analysis_Python.ipynb
Follow the instructions and code comments within the notebook for detailed steps on conducting the EDA.

Features

Data cleaning and preprocessing with Pandas.
Exploratory data analysis to uncover patterns, anomalies, or trends.
Interactive visualizations with Plotly to present findings clearly.

# Contributing

Contributions to this project are welcome. Please fork the repository and submit a pull request with your enhancements.

# License

This project is licensed under the MIT License - see the LICENSE.md file for details.