Welcome to the Pandas Basics tutorial! 🐼 This guide will introduce you to the fundamentals of using Pandas for data manipulation and analysis in Python. Whether you're new to data science or just starting with Pandas, this will be your first step into the world of efficient data handling. 😊

Why Use Pandas? 📈

Pandas is a powerful library for:

  • Data cleaning (e.g., handling missing values)
  • Data transformation (e.g., filtering, grouping)
  • Data visualization (e.g., plotting with Matplotlib)
  • Efficient storage (e.g., using DataFrames and Series)
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Getting Started 🚀

Installation

Install Pandas using pip:

pip install pandas

Or via Conda:

conda install pandas

Core Concepts 🧠

  1. DataFrame – 2D labeled data structure (like a spreadsheet)
  2. Series – 1D labeled array (like a column in a spreadsheet)
  3. Indexing – Access data using row/column labels

Example Code 💻

Here’s a simple example:

import pandas as pd

# Create a DataFrame
data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data)

# Display the DataFrame
print(df)
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Extend Your Learning 🌐

Want to dive deeper? Check out our Pandas Data Cleaning Tutorial for advanced techniques!

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