- Introduction to Matplotlib
- Importing Libraries in Python
- Dealing with Files in Python
- Making Line and Scatter Plots
- Adding Labels, Titles, Axis Ticks, and Changing Line Styles
- Rotating Axis Ticks, Adding Text and Annotations
- Adjusting Plot Sizes, Adding a Legend, and Saving the Plots
- Creating 1-Dimensional and 2-Dimensional Histograms
- Changing the Axis Scales
- Bonus Lecture: COURSE COUPON Getting lots of data
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 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
Description
Data 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.
Students also bought
Información sobre el Instructor

- 4.31 Calificación
- 40869 Estudiantes
- 3 Cursos
Maximilian Schallwig
Data Scientist
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.
Student feedback
Course Rating
Reviews
good