Welcome to the python-eda-projects repository! This project lets you analyze retail data using simple Python tools. You will uncover important trends and patterns to gain valuable business insights. Follow these steps to get started.
Before downloading, make sure your computer has the following software installed:
- Python: Version 3.7 or higher.
- Jupyter Notebook: This allows you to run the notebooks easily.
- Internet Access: To download the necessary packages and data files.
To get the files you need, visit this page: Download from Releases.
- Click the download link above to go to the Releases page.
- On the Releases page, you will see a list of versions. Look for the latest release, which will be at the top.
- Click on the version number (for example, "v1.0").
- Scroll down to find the assets section. Here you will find Jupyter notebooks and data files.
- Click on the .zip file to download it.
- Once the download is complete, locate the file in your downloads folder.
- Extract the .zip file to a location on your computer where you want to store the project.
- Open Jupyter Notebook on your computer.
- Navigate to the folder where you extracted the files.
- You will see several Jupyter notebooks. Click on any file that ends with
.ipynb. - The notebook will open in a new tab. You can run the code cells one by one by clicking on them and pressing Shift + Enter.
- Follow the instructions in the notebooks to analyze the data.
- Exploratory Data Analysis: Understand the retail dataset using common EDA techniques.
- Data Visualization: Create clear and informative graphs using libraries like Matplotlib and Seaborn.
- Easy to Follow: The notebooks guide you step-by-step through the analysis.
- Real-World Application: Gain insights that are applicable in living business scenarios.
- Learn how to manage and analyze data using Python and Pandas.
- Gain skills in creating visualizations to present data effectively.
- Understand the importance and application of EDA in businesses.
This project utilizes the following technologies:
- Python: The main programming language.
- Pandas: For data manipulation and analysis.
- NumPy: For numerical operations.
- Matplotlib & Seaborn: For creating insightful graphs and charts.
- Jupyter Notebook: An interactive platform to write and execute code.
If you have questions or suggestions, please feel free to reach out. Contributions are welcome! You can create a pull request or report issues directly on GitHub.
Happy analyzing!