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## Beyond 95%

So far we’ve generally used 95% for confidence intervals. However, this is only by convention, and we can choose any confidence interval we want. We’ve seen that the values for …

## What are errors on line plots?

Scatter plots are used to show the values of discrete data, and line plots are used to show the values of continuous data where ‘in-between’ values can be interpolated. Similarly, …

## How to compare groups of data with Python

Using different plots to compare groups of data We can use selective highlighting to compare groups of data on the same plot. We do not need to go into this …

## Line plot and bar plot

Line plots A line plot (also known as a line chart or curve chart) is a graph that displays information as a series of data points using a number line …

## How to Highlight Data With Python

Sometimes you might want to highlight selected data points on a plot with colours and highlight some data points with different colours. Other times, you might want to present data …

## Introduction to Line Plots

So far, you have been learning exclusively about scatter plots. However, of course, Seaborn also supports other types of plots. Let us investigate how Seaborn makes your life easy with …

## Relational plots

Previously, we learned to draw a scatter plot with Seaborn and to add a third dimension or variable for comparison using the hues and styles. Sometimes we might need to …

## Introduction to relational plots and subplots

So far, you learned to explore and draw scatter plots using Seaborn. However, scatter plots are not the only ones that can be created using Seaborn. There are also other …

## Using Pandas with Seaborn

Numerical plots Plots are the way for visualising the relationship between variables. These variables can either be numerical (categories such as a group, class, or division) or categorical. We will …

## Getting started with Seaborn

Before we delve any deeper and get ready for an immersive experience of learning to build plots using Seaborn, watch this video to: explore the various features of Seaborn and …