https://github.com/shaadclt/pandas-exercises
This project provides a collection of Jupyter Notebook exercises for practicing pandas, a powerful data manipulation and analysis library in Python. pandas offers a wide range of functions and methods for handling and analyzing structured data. Through this project, we aim to enhance our skills in pandas.
https://github.com/shaadclt/pandas-exercises
Last synced: 3 months ago
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This project provides a collection of Jupyter Notebook exercises for practicing pandas, a powerful data manipulation and analysis library in Python. pandas offers a wide range of functions and methods for handling and analyzing structured data. Through this project, we aim to enhance our skills in pandas.
- Host: GitHub
- URL: https://github.com/shaadclt/pandas-exercises
- Owner: shaadclt
- Created: 2022-10-19T06:44:39.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-07-08T11:12:52.000Z (about 2 years ago)
- Last Synced: 2025-02-02T09:41:23.592Z (8 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 4.86 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Pandas Exercises for Practice
This project provides a collection of Jupyter Notebook exercises for practicing pandas, a powerful data manipulation and analysis library in Python. pandas offers a wide range of functions and methods for handling and analyzing structured data. Through this project, we aim to enhance our skills in pandas and gain hands-on experience with data manipulation, exploration, and analysis.
## Prerequisites
Before running the code, make sure you have the following dependencies installed:
- Python (3.x)
- Jupyter Notebook
- NumPy
- pandas
## Getting Started
To get started with the project, follow the steps below:
1. Clone the repository:
```bash
git clone https://github.com/shaadclt/Pandas-Exercises.git
```
2. Change into the project directory:
```bash
cd pandas-exercises
```
3. Install the required dependencies:
4. Run Jupyter Notebook:
```bash
jupyter notebook
```
5. Open the Jupyter Notebook files (*.ipynb) in Jupyter.
6. Follow the instructions in the notebooks to practice and explore different pandas exercises.
## Project Overview
The project covers various pandas exercises, including but not limited to:
1. Data Loading: Loading data from different file formats, such as CSV, Excel, or JSON.
2. Data Cleaning: Handling missing values, removing duplicates, and correcting data types.
3. Data Manipulation: Filtering, sorting, aggregating, and transforming data.
4. Data Exploration: Exploring data using descriptive statistics, grouping, and pivot tables.
5. Data Visualization: Creating plots and visualizations using pandas and other libraries.
Each notebook includes explanations, code snippets, and practice exercises to reinforce the understanding of pandas concepts.
## Results and Insights
The emphasis of this project is on practicing and implementing pandas exercises rather than providing specific results or insights. Each notebook contains exercises and examples to apply the concepts learned and gain a deeper understanding of data manipulation and analysis using pandas. Feel free to experiment with different datasets, modify the exercises, or explore additional pandas functionalities beyond the provided exercises.
## Customization
You can customize the project by adding your own exercises, creating additional notebooks for specific topics, or expanding the exercises with more advanced pandas concepts. This project serves as a starting point for you to practice and enhance your skills in data manipulation and analysis using pandas.
## License
This project is licensed under the MIT License. See the `LICENSE` file for more information.
## Acknowledgments
- This project is created for the purpose of practicing pandas exercises using Jupyter Notebook.
## Contributing
Contributions are welcome! If you find any issues, have suggestions for improvements, or want to add more exercises, please open an issue or submit a pull request.