MatPlotLib with Python

MatPlotLib with Python, available at Free, has an average rating of 4.35, with 13 lectures, based on 183 reviews, and has 13022 subscribers.

You will learn about Visualize multiple forms of both 2D and 3D graphs, like line graphs, scatter plots, bar charts, and more Create live graphs Multiple Plots in a Graph PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot Customize graphs, modifying colors, lines, fonts, and more This course is ideal for individuals who are Beginner Python developers curious about Data Science It is particularly useful for Beginner Python developers curious about Data Science.

Enroll now: MatPlotLib with Python

Summary

Title: MatPlotLib with Python

Price: Free

Average Rating: 4.35

Number of Lectures: 13

Number of Published Lectures: 11

Number of Curriculum Items: 13

Number of Published Curriculum Objects: 11

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Visualize multiple forms of both 2D and 3D graphs, like line graphs, scatter plots, bar charts, and more

Create live graphs

Multiple Plots in a Graph

PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot

Customize graphs, modifying colors, lines, fonts, and more

Who Should Attend

Beginner Python developers curious about Data Science

Target Audiences

Beginner Python developers curious about Data Science

More and more people are realizing the vast benefits and uses of analyzing big data. However, the majority of people lack the skills and the time needed to understand this data in its original form. That’s where data visualization comes in; creating easy to read, simple to understand graphs, charts and other visual representations of data. Python 3 and Matplotlib are the most easily accessible and efficient to use programs to do just this.

Learn Big Data Python

Visualize multiple forms of 2D and 3D graphs; line graphs, scatter plots, bar charts, etc.

Load and organised data from various sources for visualization

Create and customize live graphs

Add finesse and style to make your graphs visually appealing

Python Data Visualization made Easy

With over 58 lectures and 6 hours of content, this course covers almost every major chart that Matplotlib is capable of providing. Intended for students who already have a basic understanding of Python, you’ll take a step-by-step approach to create line graphs, scatter plots, stack plots, pie charts, bar charts, 3D lines, 3D wire frames, 3D bar charts, 3D scatter plots, geographic maps, live updating graphs, and virtually anything else you can think of!

Starting with basic functions like labels, titles, window buttons and legends, you’ll then move onto each of the most popular types of graph, covering how to import data from both a CSV and NumPy. You’ll then move on to more advanced features like customized spines, styles, annotations, averages and indicators, geographical plotting with Basemap and advanced wire frames.

This course has been specially designed for students who want to learn a variety of ways to visually display python data. On completion of this course, you will not only have gained a deep understanding of the options available for visualizing data, but you’ll have the know-how to create well presented, visually appealing graphs too.

Tools Used

Python 3:Python is a general purpose programming language which a focus on readability and concise code, making it a great language for new coders to learn. Learning Python gives a solid foundation for learning more advanced coding languages, and allows for a wide variety of applications.

Matplotlib:Matplotlib is a plotting library that works with the Python programming language and its numerical mathematics extension ‘NumPy’. It allows the user to embed plots into applications using various general purpose tool kits (essentially, it’s what turns the data into the graph).

IDLE:IDLE is an Integrated Development Environment for Python; i.e where you turn the data into the graph. Although you can use any other IDE to do so, we recommend the use of IDLE for this particular course.

1. Matplotlib Introduction

2. PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot

3. Multiple Plots in a Graph

Course Curriculum

Chapter 1: MatPlotLib with Python

Lecture 1: Session 1. Matplotlib Introduction

Lecture 2: Matplotlib Introduction

Lecture 3: Session 2. PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot

Lecture 4: PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot

Lecture 5: Session 3. Multiple Plots in a Graph

Lecture 6: Multiple Plots in a Graph

Lecture 7: Session 4. Data Visualization using Pandas

Lecture 8: Data Visualization using Pandas

Lecture 9: What is Data Science

Lecture 10: What is Machine Learning

Lecture 11: Summary

Instructors

DATAhill Solutions Srinivas Reddy
Data Scientist

Rating Distribution

1 stars: 20 votes

2 stars: 25 votes

3 stars: 46 votes

4 stars: 53 votes

5 stars: 39 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!