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python_module_pandas

This repository contains interactive Jupyter notebooks that cover the core functionalities of the Pandas library for data manipulation and analysis.

📘 Contents

  • 1. basic_operation.ipynb
    Introduction to basic Pandas operations like creating Series and DataFrames, indexing, and slicing.

  • 2. dataframe_basics.ipynb
    Explores DataFrame structure, column operations, data types, and useful attributes.

  • 3. read_write.ipynb
    Demonstrates reading from and writing to CSV and other file formats using Pandas.

  • 4. handling_missing_data.ipynb
    Techniques to detect, handle, and impute missing data.

  • 5. grouping_data.ipynb
    Introduction to groupby for aggregation, transformation, and filtering of data.

  • 6. data_concatenation_merging.ipynb
    Covers combining datasets using concatenation, merging, and joins.

🔧 Requirements

  • Python 3.x
  • pandas
  • jupyter
  • numpy
  • matplotlib (optional for visual inspection)

Install them using:

pip install pandas numpy matplotlib jupyter

🚀 Getting Started

  1. Clone or download the repository.
  2. Launch Jupyter Notebook or JupyterLab.
  3. Open and run the notebooks in sequence.

📂 Dataset

  • IMDB Top 250 Movies.csv
    A dataset used in examples to demonstrate real-world data manipulation.

🔑 Keywords

python pandas data-wrangling data-analysis jupyter-notebook dataframe csv groupby missing-data merge eda

📜 License

This project is licensed under the MIT License.