Python Pandas Tutorial

Working with text data is one of the most common and essential parts of data analysis. In real-world datasets—whether it’s

Reshaping Data with stack() and unstack() in Pandas 1. Introduction While melt() and pivot reshape DataFrames between wide and long

1. Introduction In real-world datasets, information is often stored in a wide format, where each column represents a variable. While

Pivoting and pivot tables are powerful tools in Pandas that help reshape and summarize data. They allow us to transform

Handling missing data is an essential step in data cleaning and preprocessing. Real-world datasets often contain gaps due to errors,

Excel files (.xls, .xlsx) are one of the most common formats for sharing tabular data. Pandas makes it very simple

Python Pandas Tutorial — Chapter 3: DataFrames Basics In the last chapter, we explored Series (1D labeled data). Now we

Welcome! This chapter gives a practical, hands-on introduction to pandas — the essential Python library for data manipulation and analysis.