🐼Pandas Tutorial Series

Welcome to the Pandas Tutorial Series! This collection of Jupyter notebooks is designed to help you learn and master Pandas, the powerful Python library for data manipulation and analysis.

What You'll Learn

Starting from the basics, each notebook guides you through essential Pandas concepts and techniques, gradually moving to more advanced topics. The tutorials are beginner-friendly, with clear explanations, practical examples, and hands-on exercises to reinforce your learning.

Getting Started

Clone the repo:

git clone https://github.com/kunjjarsaniya/Pandas.git
cd Pandas

Tutorial Notebooks

1. 1_Series.ipynb
   Learn about Pandas Series, a one-dimensional labeled array. Discover how to create Series from lists, dictionaries, and custom indices.

2. 2_DataFrames.ipynb
   Dive into DataFrames, the two-dimensional labeled data structure. Learn how to create, access, and manipulate DataFrames effectively.

3. 3_MissingData_.ipynb
   Master techniques to detect, handle, and fill missing data in your datasets.

4. 4_Merging_Joining_Concatenation.ipynb
   Understand how to combine DataFrames using merging, joining, and concatenation methods.

5. 5_GroupByAggregation.ipynb
   Explore the GroupBy functionality to group data and perform aggregate operations.

6. 6_PivotTables.ipynb
   Learn to create and use pivot tables for summarizing and analyzing data.

7. 7_Operations.ipynb
   Perform arithmetic and comparison operations on DataFrames and Series.

8. 8_FeatureExtraction.ipynb
   Discover techniques for extracting meaningful features from your data for analysis and modeling.

9. 9_Countries.ipynb
   Apply your Pandas skills in a practical example using country data.

Sample Data Files

• anime.csv
• Countries.csv

These datasets are used throughout the tutorials to demonstrate data manipulation techniques.

How to Use This Series

Follow the notebooks in order to build your knowledge step-by-step. Each tutorial builds on the previous one, helping you develop a solid understanding of Pandas.

Consistent Look and Feel

All notebooks share a consistent style and theme to provide a smooth and cohesive learning experience.

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Dependencies for Pandas Tutorial Series

To run the Pandas tutorial notebooks smoothly, make sure you have the following dependencies installed:

Required Packages

• Python 3.6 or higher
• pandas
• jupyter notebook

Optional but Recommended

• numpy (for numerical operations)
• matplotlib or seaborn (for data visualization)

Installation Instructions

You can install the required packages using pip. Run the following command in your terminal or command prompt:

pip install pandas jupyter numpy

Running the Notebooks

1. Navigate to the Pandas folder in your terminal.
2. Start Jupyter Notebook by running:

jupyter notebook

3. Open the notebook files (.ipynb) in your browser and start learning!

If you encounter any issues or need help with installation, please refer to the official documentation of each package.

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Happy learning and happy coding with Pandas!