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Python DataFrame Basics

This project contains a beginner‑friendly Jupyter notebook that demonstrates 10 essential pandas DataFrame operations, including:

  1. Creating a DataFrame
  2. Printing the DataFrame
  3. Viewing columns
  4. Viewing the first rows (head())
  5. Selecting a column
  6. Adding a new column
  7. Filtering data
  8. Reading a CSV file
  9. Understanding indexes
  10. Sorting your data

The notebook is designed for learning, teaching, and demonstrating foundational Python data analysis skills.

📁 Files Included

dataframe_basics.ipynb
The main notebook with step‑by‑step examples and explanations for each pandas concept.

sample_data.csv
A small dataset used in the notebook to demonstrate reading CSV files into pandas.

desktop.ini
A Windows-generated file. Safe to ignore — it does not affect the project.

🚀 How to Run This Notebook

  1. Install Python 3.11+
  2. Install pandas and Jupyter (if needed):
    pip install pandas jupyter
  3. Open the notebook in VS Code, Jupyter Notebook, or JupyterLab
  4. Select a Python kernel
  5. Click Restart Kernel and Run All to reproduce the results from top to bottom

🎯 Purpose of This Project

This notebook supports:

  • Practicing foundational Python + pandas skills
  • Teaching beginners how to work with DataFrames
  • Creating micro‑learning content (TikTok / LinkedIn posts)
  • Building a data-focused portfolio
  • Demonstrating clean, reproducible workflows in Jupyter

📬 Contact

LinkedIn: https://www.linkedin.com/in/vivianferguson
GitHub: https://github.com/mrvivian