Data Visualization with Python and New Methods in Matplotlib

Data Visualization with Python and New Methods in Matplotlib, available at $49.99, has an average rating of 4.3, with 39 lectures, based on 87 reviews, and has 24401 subscribers.

You will learn about 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 This course is ideal for individuals who are Developers or Data Analysts or Data Scientists or Students or Researchers or Managers It is particularly useful for Developers or Data Analysts or Data Scientists or Students or Researchers or Managers.

Enroll now: Data Visualization with Python and New Methods in Matplotlib

Summary

Title: Data Visualization with Python and New Methods in Matplotlib

Price: $49.99

Average Rating: 4.3

Number of Lectures: 39

Number of Published Lectures: 39

Number of Curriculum Items: 39

Number of Published Curriculum Objects: 39

Original Price: $89.99

Quality Status: approved

Status: Live

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

Who Should Attend

Developers

Data Analysts

Data Scientists

Students

Researchers

Managers

Target Audiences

Developers

Data Analysts

Data Scientists

Students

Researchers

Managers

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

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!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Creating 3D Bar chart

Lecture 1: Creating 3D Bar Chart

Lecture 2: Codes

Chapter 3: Creating 3D Histogram

Lecture 1: Creating 3D Histogram

Lecture 2: Codes

Chapter 4: Creating 3D Contour Plots

Lecture 1: Creating 3D Contour Plots

Lecture 2: Codes

Chapter 5: Wireframes and Surface Plots

Lecture 1: Creating Wireframes and Surface Plots

Lecture 2: Codes

Chapter 6: Creating 3D Points and Lines

Lecture 1: Creating 3D Points and Lines

Lecture 2: Codes

Chapter 7: Surface Triangulations

Lecture 1: Surface Triangulations

Lecture 2: Codes

Chapter 8: Mobius strip

Lecture 1: M?bius strip

Lecture 2: Codes

Chapter 9: Creating 3D Scatter Plot

Lecture 1: Create 3D Scatter Plot using Matplotlib and Numpy

Lecture 2: Codes

Chapter 10: Creating 3D Line Graphs

Lecture 1: Create 3D Line Graphs using Numpy and Matplotlib library

Lecture 2: Codes

Chapter 11: Creating 3D Surface and Gradient Surface Plot

Lecture 1: How to Plot 3D Surface and Gradient Surface Graph

Lecture 2: Codes

Chapter 12: Creating 3D Wireframe Graph

Lecture 1: Plotting a Simple Wireframe Graph

Lecture 2: Creating Multiple Wireframe Graphs in the Same Plot

Lecture 3: Codes

Chapter 13: Draw Polar Scatter Plot

Lecture 1: Plotting Scatter Plot in Polar Coordinates

Lecture 2: Plotting Sine Function in the polar plot

Lecture 3: Plotting Scattered Tangent Function in a Polar Plot

Lecture 4: Plotting Scattered Logarithmic Graph in a Polar Plot

Lecture 5: Codes

Chapter 14: Draw a Polar Contour Plot in Matplotlib

Lecture 1: Plot a Polar Contour Plot

Lecture 2: Plot Multiple Contour Plot

Lecture 3: Plotting Polar Contour Plot of Fetching Dataset

Lecture 4: Codes

Chapter 15: Create Heatmaps using Python Folium

Lecture 1: Interesting Heatmaps using Folium

Lecture 2: Requirments

Lecture 3: Generate Heatmap

Lecture 4: Generate Heatmap with Time

Lecture 5: Codes

Lecture 6: The End

Instructors

S. Emadedin Hashemi
AI Expert and Data Scientist

Rating Distribution

1 stars: 3 votes

2 stars: 2 votes

3 stars: 8 votes

4 stars: 20 votes

5 stars: 54 votes

Frequently Asked Questions

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