Data Visualization with Python for Beginners (Udemy.com)

Learn how to start visualizing all your data directly in your code

( 96 Reviews )

Created by: Maximilian Schallwig

Produced in 2017

What you will 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 changing line styles
Customize your axis by changing 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

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 86 / 100

Course Description

ata and analytics are becoming increasingly important in our world and in modern day businesses. To start off with data analytics (and ultimately provide nice images of our results), we need to be able to plot our data, preferably in the way we imagine it in our heads.

Matplotlib provides many great plotting opportunities and methods for data visualization, and in this course we will be looking at some introductory methods for getting started with creating plots in Python.

Once we have a starting point for plotting data we can easily expand our knowledge to different areas to make sure we can best represent all of our data. Who this course is for:
Anyone interested in analyzing dataAnyone who needs to visualize dataPeople who want to incorporate data visualization into their codeAnyone who is interested in expanding their Python knowledge

Time: 1.5h

Instructor Details

Maximilian Schallwig

4.3 Rating
96 Reviews

I've worked for over two years in physics research and mathematical analysis. I participated in two international physics competitions, where my two teammates and I won silver and gold. My thesis was in the field of Quantum Biology, focusing on analyzing the behavior of excitons at room temperature with electronic interaction.
Due to my affinity for math and statistics from my studies in physics, I tend towards data mining, processing, and analysis, which are also the things that I find most exciting.
I enjoy learning new methods and developing my skills, and am constantly studying new literature and documentation to find exciting material that can be applied in the field of data analysis.

If you want to keep up with what else I'm doing in the fields of programming, data, and data science, you can check me out at codingwithmax.