Complete Course on Data Visualization, Matplotlib and Python

Master Matplotlib Anatomy and Learn Seaborn to Visualize Data with Custom, Beautiful Charts, Suitable for All Purposes

4.48 (5152 reviews)
Udemy
platform
English
language
Development Tools
category
instructor
Complete Course on Data Visualization, Matplotlib and Python
14,097
students
3.5 hours
content
Mar 2018
last update
$79.99
regular price

What you will learn

Learn Matplotlib Anatomy

Customize charts of any complexity with ease

Create a variety of charts, Bar Charts, Line Charts, Stacked Charts, Donut and Pie Charts, Histograms, KDE plots, Violinplots, Boxplots, Auto Correlation plots, Scatter Plots, Heatmaps

Feel comfortable managing various Matplotlib Artists such as Legends, Annotations, Texts, Patches, Lines, Collections, Containers, Axis

Create statistical charts with Seaborn

Visualize data with Matplotlib in OOP

Dual Axis Charts

Description

COURSE IN THE NUTSHELL

  1. Concise and to the point, as I appreciate your time and don't have the luxury to tell you my story

  2. Easy to understand and tailored for a broad audience, as it only requires a basic knowledge of Python and only

WHAT STUDENTS SAY

"This is a great course! Bekzod's instruction is very clear and concise. I went from having zero knowledge of Matplotlib to creating highly customized visualizations within hours. Prerequisites in Python and Pandas are not necessarily needed but understanding the basics in both will maximize your experience in this course. I recommend to open a blank notebook and following along with Bekzod, pausing along the way read the help documentation he references, as well as read any code snippets you may not understand right away. It takes a little longer to finish the course but it's more than worth it. I'm looking forward to additional courses offered by Bekzod." - Jeff Dowden

"I learn a lot from the lesson until now. This lesson improves my understanding of OOP. It is so easy, interesting and amazing to use python to visualize data from the perspective of OOP." - Haitao Lyu

"This course is completely amazing. Direct to the point and use real data not simulation with numpy as usually others did. Great job Bekzod!! " - Hartanto

"'I've used Matplotlib and Seaborn for a number of years. I was reviewing this to see if it was a good introduction for people I work with. The answer, yes. It's a very good introduction that covers some of the critical details necessary to navigate Matplotlib in order to customize plots." - Stephen Basco

TELL ME MORE...

After completing this course you will master Matplotlib on an intuition level and feel comfortable visualizing and customizing Matplotlib, Seaborn and Pandas charts of any complexities. More specifically, this course is a great resource if you are interested in:

  1. How Matplotlib Works

  2. How to create charts from simple to scientific ones with Matplotlib, Pandas and Seaborn

  3. How to customize charts of any complexities with ease

To achieve the objectives, I split this course into the following sections:

Matplotlib Anatomy

As the name implies, in this section you will learn how Matplotlib works and how a variety of charts are generated. 

It gives you a solid understanding and a lot of aha-moments when it comes to creating and / or customizing charts that you haven't dealt with before.

Create 2D Charts

In this section, you will generate plethora of charts using Matplotlib OOP, and Pandas and mix them together to achieve the maximum efficiency and granular control over graphs.

Axes Statistical Charts

Here we will learn how to make statistical charts such as Auto Correlation, Boxplots, Violinplots and KDE plots with Matplotlib OOP and Pandas.

Seaborn

Seaborn, a high-level interface to Matplotlib helps make statistical plots with ease and charm. It is a must-know library for data exploration and super easy to learn. And in this section, we will create Regression plots, Count plots, Barplots, Factorplots, Jointplots,  Boxplots, Violin plots and more.

Course Summary and Exercises

This section has dual purposes. 

For one, it is a good summary of the course and provides you with exercises to test your knowledge and then provide solutions for comparison.

Secondly, If you are short-on time, you can start here and then move to other sections if you seek more granular coverage of the topic or when you have more time available.

TOOLS USED

  1. Jupyter Notebook (IDE)

  2. Matplotlib 2.x

  3. Seaborn 0.8.1 or above

  4. Pandas 0.22 or above

Content

INTRODUCTION

Introduction
Instructor's message
Matplotlib Anatomy
What you will need

MATPLOTLIB ANATOMY

Line2D: Add Lines
Line2D: Properties
Rectangle: Add Patches
Rectangle: Properties
FancyBboxPatch: Properties
Text: Add Text
Text: Properties
SINGLE QUESTION QUIZ
Annotations: Add Text
Annotations: Properties
Legends: Add Legends
Legends: Properties
SINGLE QUESTION QUIZ
Axis: Labels and Spines
QUIZ TIME
Axis: Ticks
Axis: Tick Formatters and Locators

CREATE 2D CHARTS

Line charts
Bar charts: Basics
Bar charts: Grouped
Bar charts: Stacked
Scatter plots
Pie charts
Donut charts
Histograms
Polar charts
Dual Axis charts

AXES STATISTICAL CHARTS

Autocorrelation
KDE plots
Boxplots
Violinplots
Heatmap and Colorbar

SEABORN

Regplot
Countplot
Barplot
Boxplot
Violinplot and Swarmplot
Factorplot
Distplot
Jointplot
Pairplot

COURSE SUMMARY & EXCERCISES

Legends
Ticks
Patches
Lines
Annotations
PathCollections (Scatter Plot Markers)
Axes Spines

Reviews

Margarita
November 7, 2023
Useful content. The basics could be explained a little better. Ex. Why does the code need to be set up the way it is. Does not feel very beginning friendly. Also, it would be useful to be able to download the notebooks to follow along more easily.
Tojo
November 2, 2023
Content is great. This "the teacher is coding with you" is the best way to teach (when it's about code), the tutor should not speed up the video though. This "coding with you" style aims to give the feeling that you and the teacher are in the same pace. Though, you cannot code with the tutor without pausing the video or just writting things in a rush ... Same as just showing something already coded in advance.
Giorgos
September 14, 2023
Some of the arguments in the functions is deprecated, and need some updating to do. Another issue was the speed of the lectures. This speed requires the notebooks to be provided (maybe with some key-variables missing and must be filled by us) and follow through the course. All in all, nice effort and course, with potential to be better.
Kathleen
August 25, 2023
Informative and useful. This is an older couse and some of the methods have been changed in later versions of matplotlib and seaborn so some of the exercises do not work well.
Akash
August 22, 2023
No explanation of the elements and objects used in the lecture, even there is no clear instructions provided to how to install all the software. the teaching style of instructor is very poor and i can say the course is for the intermediate or advanced professionals but not beginners.
Fadwa
July 31, 2023
yes but the teacher went too fast, often without explaining what he was doing. He should have before explained what the function does and then procede with the code.
Sham
June 11, 2023
Please explain in briefly when you used command when apply directly e are not able to understand what actually you done
Stephen
May 23, 2023
THE GOOD: The course provides a lot of information. This is a good refresher course for someone who specializes in data visualization plus new information especially on how to make graphs colorful and more detailed. THE BAD: Instructor rushes a lot and it's really hard to keep up. Would be better if there were more data science related data visualization practice.
Saurabh
May 8, 2023
The training doesn't conform to the initially mentioned comments that no coding knowledge is required This also requires knowledge check at each level
Deivison
May 2, 2023
The key point in the introduction video was how "beginner friendly", "no copy/paste only common sense" this course would be. Right off the start, in the first lesson "Line2D: Add Lines" there is a bunch of code without any explanation where someone without a background would need to copy/paste. Also, the fast-forwarding bits are extremely annoying, even though that it's "not worth material" it distracts quite a bit. Maybe this is a very good course if you already have a background and a basic experience, but as someone new this is not what I was expecting, at all.
Soumyadeep
February 7, 2023
This is the starting of the course and this provides an overall idea of the course hence this can be an informative session.
Dan
February 1, 2023
Was good. Both the matplotlib and seaborn sections had a lot of places where the API just no longer works the same. It was good for 90% of it, but the rest of it rather than being able to actually run anything, you just have to watch. I could figure out whatever the current API is, but since no keyword arguments are used anywhere(??), it is hard to know what some values stand for. like this for the seaborn regplot() - using the provided notebook: --------------------------------------------------------------------------- TypeError Traceback (most recent call last) Cell In [4], line 3 1 # So, our first scatter plot with 2 # a linear fitting model ----> 3 sns.regplot('Sepal length','Petal width', 4 data=d, 5 scatter=True, # this is the default option 6 fit_reg = True, # turn on/off fitting line 7 order = 1, # for polynomial regression 8 n_boot=10, 9 truncate=True, 10 x_jitter = 0, 11 y_jitter=0, # should line fill x axis or not 12 marker='^', 13 scatter_kws=dict(edgecolor='r',lw=2, facecolor='w', s=50), 14 line_kws=dict(color='g', linestyle='dashed'), 15 ci=0 16 17 ) 19 ax = plt.gca() 20 fig = plt.gcf() TypeError: regplot() got multiple values for argument 'data' --- no idea whatsoever what the first two arguments stand for. "data" now must be the first argument in the new API. I could go and search for the old API documentation, but ... gets kind of pointless to debug a class example
Tahlia
December 8, 2022
Instructor went very fast, had to keep pausing the video so I could keep up with typing. Wasn't very enjoyable
Sadaqat
November 5, 2022
Maybe you are trying to set the stage. But you teach lots of good stuff but without any coherence among the flow. It should be taught step by step from simple to complicated. You showcase many techniques without any background so basically i have memorize not do it as intuitive process. But maybe you will come to this later in the course, i dont want to make a judgement too quick.
Jacob
October 19, 2022
Says no coding experience needed but then uses relatively complex Python concepts, some parts go way too fast (and I generally prefer a faster lecturing speed but this is too much)

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1510692
udemy ID
1/15/2018
course created date
10/31/2020
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