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.