• Post category:StudyBullet-14
  • Reading time:7 mins read

Step-by-step training for 3D and advanced visualization in python and Matplotlib (with all the codes)

What you will learn

Designing and illustrating figures and plots in 3D

Familiarity with Python libraries for data visualization

Knowledge of new and practical diagrams to visualize data in different fields

Create functions needed to draw plots professionally

Familiarity with creating, collecting and preparing data for visualization


Due to the importance of data visualization, there are many pieces of training on this subject that teach basic and preliminary data visualization. But in this course, we will teach you how to visualize your data in an advanced way in Python. In this course, we even teach 3D visualization so that you can specifically visualize your data and draw graphs using Python codes.

You can use this course to visualize your data for managers, scientific papers, work projects, university classes, personal websites, and even advertisements.

In today’s world, a lot of data is being generated on a daily basis. And sometimes to analyze this data for certain trends, and patterns may become difficult if the data is in its raw format. To overcome this data visualization comes into play. Data visualization provides a good, organized pictorial representation of the data which makes it easier to understand, observe, and analyze. In this course, we will discuss how to advanced visualize data using Python.

This is just one demonstration of the usefulness of data visualization that makes it so popular in data science. Let’s see some more reasons why data visualization is so important:

1. Data Visualization Discovers the Trends in Data

2. Data Visualization is Interactive

3. Data Visualization Provides a Perspective on the Data

4. Data Visualization Explains a Data Process

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5. Data Visualization Strokes the Imagination

6. Data Visualization Tells a Data Story

7. Data Visualization Puts the Data into the Correct Context

8. Data Visualization is Educational for Users

9. Data Visualization Saves Time

10. Data Visualization Presents Data Beautifully

All of these reasons demonstrate the importance of data visualization in data science. Basically, it is a much more user-friendly method to understand the data and also demonstrates the trends and patterns in the data to other people. And it doesn’t hurt that data visualization is beautiful to look at and so more appealing to people than rows of boring data!





Creating 3D Bar chart

Creating 3D Bar Chart

Creating 3D Histogram

Creating 3D Histogram

Creating 3D Contour Plots

Creating 3D Contour Plots

Wireframes and Surface Plots

Creating Wireframes and Surface Plots

Creating 3D Points and Lines

Creating 3D Points and Lines

Surface Triangulations

Surface Triangulations

Mobius strip

Möbius strip

Creating 3D Scatter Plot

Create 3D Scatter Plot using Matplotlib and Numpy

Creating 3D Line Graphs

Create 3D Line Graphs using Numpy and Matplotlib library

Creating 3D Surface and Gradient Surface Plot

How to Plot 3D Surface and Gradient Surface Graph

Creating 3D Wireframe Graph

Plotting a Simple Wireframe Graph
Creating Multiple Wireframe Graphs in the Same Plot

Draw Polar Scatter Plot

Plotting Scatter Plot in Polar Coordinates
Plotting Sine Function in the polar plot
Plotting Scattered Tangent Function in a Polar Plot
Plotting Scattered Logarithmic Graph in a Polar Plot

Draw a Polar Contour Plot in Matplotlib

Plot a Polar Contour Plot
Plot Multiple Contour Plot
Plotting Polar Contour Plot of Fetching Dataset

Create Heatmaps using Python Folium

Interesting Heatmaps using Folium
Generate Heatmap
Generate Heatmap with Time