Chapter 6: Pie Charts in Matplotlib
Pie charts are a popular way to represent parts of a whole. They divide a circle into slices, where each […]
Chapter 5: Scatter Plots in Matplotlib
Scatter plots are one of the most important tools in data visualization. They show the relationship between two variables by
Chapter 4: Histograms in Matplotlib
Histograms are a type of plot used to visualize the distribution of a dataset. Unlike bar plots, which show categorical
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,