What you'll learn

Make line plots in Python

Make scatter plots in Python

Make 1-dimensional and 2-dimensional histogram plots

Customize your plots by adding colour and chag line styles

Customize your axis by chag the tick labels

Add custom titles and labels to your plots

Add custom text to your plots

Adjust the size of your figures

Add a legend to your plots

Be able to save your figures in a desired format to your computer

Change the scale of the axis to better graph logarithmic data

Requirements

Basic Python knowledge

A Python 3 Environment to Code in

Description

Usually data analytics at one point or another also means including or creating graphics. This can help you get a better sense of the data as well as help you better communicate your findings to others.

Python is a favourite among data professionals, and perfog analytics in Python is becoming increasingly more common. Therefore, it's great to be able to also directly create custom graphs alongside all the analytics.

In this course we'll start with some basic setup, and then get into different types of plots that we can create as well as how we can customize them.

We'll start off covering basic line and scatter plots, just to get a hang of the library, and then move further to create a larger variety of graphs. You'll learn how to add error bars, how to use and represent colours for intensities, how to use images in your plots, as well as how to create 3d plots.

Additionally, we'll spend some looking at the customization options that Matplotlib provides, so that we can change the way our axes and axis ticks and labels look, learn how to add annotations and math formulas, or also how to hide parts of a graph so that we have a reduced and cleaner version.

Who this course is for:

Anyone interested in analyzing data

Anyone who needs to visualize data

People who want to incorporate data visualization into their code

Anyone who is interested in expanding their Python knowledge




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