Chapter 3 – Bar Plots in Matplotlib
Bar plots (or bar charts) are used to represent categorical data with rectangular bars. The length or height of the […]
Chapter 2: Line Plots in Matplotlib
Line plots are one of the most common types of plots in data visualization. They are used to display trends
Chapter 1: Introduction to Matplotlib
Matplotlib is one of the most popular Python libraries for data visualization. Whether you’re exploring data, building dashboards, or preparing
Pandas stack() and unstack() Methods
Reshaping Data with stack() and unstack() in Pandas 1. Introduction While melt() and pivot reshape DataFrames between wide and long
Pandas Melt method
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 in Pandas
Pivoting and pivot tables are powerful tools in Pandas that help reshape and summarize data. They allow us to transform
Pandas – Handling Missing Data (fillna, dropna, interpolate)
Handling missing data is an essential step in data cleaning and preprocessing. Real-world datasets often contain gaps due to errors,
Pandas Read or write to excel
Excel files (.xls, .xlsx) are one of the most common formats for sharing tabular data. Pandas makes it very simple
Pandas DataFrames Basics
Python Pandas Tutorial — Chapter 3: DataFrames Basics In the last chapter, we explored Series (1D labeled data). Now we
Python Pandas Tutorial
Python Pandas Series Basics
Python Pandas Tutorial — Chapter 2: Series Basics In the previous chapter, we introduced pandas and its two main data