MatPlotLib for Python Developers – Advanced

Learn about advanced level topics and how to leverage them to draft solutions for plotting based problems

We will be covering all the advanced level concepts in the course by the virtue of the sample questions which have been included to help the trainees on getting a precise view of the topics. You will get to learn about all the advanced-level topics and will also learn how to leverage them to draft solutions for plotting-based problems. Once you are done with this unit, you will be able to work proficiently with all the aspects of Matplotlib. We will be covering the following:

What you’ll learn

  • Learn Path with Effect, Transformation Tutorial, Colors in Matplotlib and Colormap Normalization.
  • Learn Choosing Colormaps, Text in Matplotlib, Annotations and Writing Mathematical Expression.
  • Learn Typesetting, Text Rendering and Toolkits.

Course Content

  • Introduction –> 1 lecture • 3min.
  • Path with Effect –> 3 lectures • 27min.
  • Transformation Tutorial –> 3 lectures • 27min.
  • Colors in Matplotlib –> 4 lectures • 41min.
  • Colormap Normalization –> 3 lectures • 26min.
  • Choosing Colormaps –> 4 lectures • 36min.
  • Text in Matplotlib –> 4 lectures • 36min.
  • Annotations –> 6 lectures • 55min.
  • Writing Mathematical Expression –> 2 lectures • 13min.
  • Typesetting –> 2 lectures • 16min.

MatPlotLib for Python Developers – Advanced

Requirements

  • There are a few things that you should be supposed to know before you can start learning about MatPlotLib. The very first thing is, you should know python fundamental. As MatPlotLib is a python library, you are supposed to know how does python works so that you can bring this library in use while developing a program in python. If you are already working as a python developer, you might find it very easy to learn python while if you are a beginner, you will need to give some time practicing it so that you can understand everything perfectly..
  • The knowledge of graphical representation of data using the mathematical formulas is the next important thing that one should know to make their learning easy. The graphs plotted using this library runs the mathematical formula in the background so that the appropriate graph could be generated using the available data. It is not that mandatory to know everything about the formulas as python is already there for you, but having a basic idea will always help you to make the learning fun. You can have an overall look at the formulas present there in the python that you will be using throughout these MatPlotLib Tutorials..

We will be covering all the advanced level concepts in the course by the virtue of the sample questions which have been included to help the trainees on getting a precise view of the topics. You will get to learn about all the advanced-level topics and will also learn how to leverage them to draft solutions for plotting-based problems. Once you are done with this unit, you will be able to work proficiently with all the aspects of Matplotlib. We will be covering the following:

  • Path with Effect
  • Transformation Tutorial
  • Colors in Matplotlib
  • Colormap Normalization
  • Choosing Colormaps
  • Text in Matplotlib
  • Annotations
  • Writing Mathematical Expression
  • Typesetting
  • Text Rendering and Toolkits

MatPlotLib may be defined as the python library that is used to implement the functionality of the graphical representation of data in the application developed in python. It consists of several components that help us to plot a two-dimensional graph using the python script. By using Numpy one can implement the multi-dimensional graph as well. In actual terms, it offers us the API which is further used together with python to get the graph generated using the data available. It is used in creating an enterprise-based application that helps in making a business decisions.

To understand MatPlotLib, let go ahead with an illustration. Suppose we are required to develop a python based application that uses the data store in its backend to generate a graph dynamically. We always have an option to embed a static graph that doesn’t change following the data, but when it comes to having a dynamic graph generated, we leverage this library. We can use the various components of MatPlotLib which will help us to plot a two-dimensional or multidimensional graph that will be used while graphically presenting the data. The application will be then ready to present all the collected data in an informative manner, making it very easy for the decision-makers to use it.