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Pandas basics for data manipulation: Filtering, grouping, sorting, and adding new columns using Python’s Pandas library.

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Pandas Basics for Data Manipulation

This repository contains a Jupyter Notebook showcasing basic data manipulation operations using Python's Pandas library. It covers key concepts like filtering, sorting, grouping, and modifying DataFrames.

Project Overview

The goal of this notebook is to build a solid foundation in Pandas, focusing on core functions essential for data analysis and manipulation.

Features

  • Filtering: Selecting rows based on conditions.
  • Sorting: Ordering data by columns.
  • Grouping: Calculating group-level statistics.
  • Adding Columns: Creating new columns using calculated values.

Tech Stack

  • Python 3.9+
  • Pandas library
  • Jupyter Notebook

Usage

Run each code cell in the Jupyter Notebook to explore Pandas operations step by step. Modify the dataset and experiment with different functions to deepen your understanding.

Screenshots

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Feel free to suggest improvements or raise issues for discussion!

Author

Sushma Sandanshiv

For any questions or collaboration opportunities, connect with me on LinkedIn.

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Pandas basics for data manipulation: Filtering, grouping, sorting, and adding new columns using Python’s Pandas library.

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