Annotating barplots with labels like texts or numerical values can be helpful to make the plot look better. Till now, one of the options add annotations in Matplotlib is to use pyplot’s annotate() function. Starting from Matplotlib version 3.4.2 and above, we have a new function, axes.bar_label() that lets you annotate barplots with labels easily.… Continue reading How To Annotate Barplot with bar_label() in Matplotlib
Connect Paired Data Points in a Scatter Plot in Python (Step-by-Step Guide)
Want to connect paired data points in a scatter plot using Matplotlib? This step-by-step tutorial shows you how to draw lines between paired observations so you can easily visualize before–after comparisons, longitudinal changes, and repeated-measures data. We cover four practical methods — a simple plot() + scatter() combo, looping through groups, efficient LineCollection rendering, and… Continue reading Connect Paired Data Points in a Scatter Plot in Python (Step-by-Step Guide)
How to Add Legend to Scatterplot Colored by a Variable with Matplotlib in Python
Matplotlib, one of the powerful Python graphics library, has many way to add colors to a scatter plot and specify legend. Earlier we saw a tutorial, how to add colors to data points in a scatter plot made with Matplotlib‘s scatter() function. In this tutorial, we will learn how to add right legend to a… Continue reading How to Add Legend to Scatterplot Colored by a Variable with Matplotlib in Python
Visualizing Missing Data with Barplot in R
One of the first and most critical steps in any data exploration project is understanding the extent of missing data. Missing values, or NAs, can significantly impact your analysis and modeling results. While there are a few quick ways to visualize missing data, one of the most intuitive is the stacked bar plot. In this… Continue reading Visualizing Missing Data with Barplot in R
Visualizing Missing Data with Seaborn Heatmap and Displot
Understanding the level of missing data in the data set analysis should be one of the first things we all should do while doing data analysis. In this post, we will use Python’s Seaborn library to quickly visualize how much data is missing in a data set. One of the ways to visualize the missing… Continue reading Visualizing Missing Data with Seaborn Heatmap and Displot