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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 …

Introduction to highlighting the data

Before we delve any deeper and get ready for an immersive experience of learning different features of styling and visualising the data creatively in data analytics, uncover the concepts of …

Confidence bands

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, …

Comparing groups of data

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 …

Highlighting data

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 …

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 …

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 …

Seaborn on your system

Seaborn plots values from standard Pandas data structures. It is included with Anaconda, so if you’ve decided to use Anaconda to complete this course, there’s no need to install anything. …

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 …

Introduction to uncertainty and errors in data

Before we start learning how to display uncertainty using Python, watch this video to: familiarise yourself with the constant changes in errors and uncertainty understand the various methods of preparing …

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 …

Introduction to uncertainty and errors in data

Before we start learning how to display uncertainty using Python, watch this video to: familiarise yourself with the constant changes in errors and uncertainty understand the various methods of preparing …

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 …