The Complete Data Visualization with Python [2022]

The Complete Data Visualization with Python [2022], available at $49.99, has an average rating of 4.5, with 44 lectures, based on 6 reviews, and has 73 subscribers.

You will learn about Matplotlib Pandas Numpy Plotly Dash 3D-plotting 4D-plotting Slider KDE plots Violin plots Joint plots Heatmaps Bar Chart Pie Chart lm plots Bubble_plot This course is ideal for individuals who are You should take this course if you want to become a Data Scientist or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills It is particularly useful for You should take this course if you want to become a Data Scientist or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills.

Enroll now: The Complete Data Visualization with Python [2022]

Summary

Title: The Complete Data Visualization with Python [2022]

Price: $49.99

Average Rating: 4.5

Number of Lectures: 44

Number of Published Lectures: 44

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Matplotlib
Pandas
Numpy
Plotly
Dash
3D-plotting
4D-plotting
Slider
KDE plots
Violin plots
Joint plots
Heatmaps
Bar Chart
Pie Chart
lm plots
Bubble_plot

Who Should Attend

You should take this course if you want to become a Data Scientist or if you want to learn about the field
This course is for you if you want a great career
The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

Target Audiences

You should take this course if you want to become a Data Scientist or if you want to learn about the field
This course is for you if you want a great career
The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

This course will give you resources to learn python and effectively use it to analyze and visualize data! Start your career in Data Science!

You’ll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data.

You will also get lifetime access to many python code notebooks, new and updated videos, as well as future additions of various data analysis projects that you can use for a portfolio to show future employers!

By the end of this course you will:

– Have an understanding of how to program in Python.

– Know how to create and manipulate arrays using NumPy and Python.

– Know how to use pandas to create and analyze data sets.

– Know how to use matplotlib and seaborn libraries to create beautiful data visualization.

– Have an understanding of many other plots such as lm plots, Bubble plots, and many other kinds of plots which will not be covered in any other course.

– Have an understanding of plotly and dash and how to use them in the most efficient way.

– Know how to perform 3D and 4D plots.

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There are more than 5 projects for you to practice. These projects are listed below:

World Health Report project.
Poverty Statistics Data project.
Google Play Store dataset project.
HPI dataset Project.
Universities dataset Project.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Structure

Lecture 2: How to make out of this course

Chapter 2: Fundamental Visualization

Lecture 1: Introduction to the section

Lecture 2: Line chart

Lecture 3: Bar chart

Lecture 4: Advanced Bar chart

Lecture 5: Grouped Bar chart

Lecture 6: Pie plot

Lecture 7: Two pie charts on a single graph

Lecture 8: Scatter plot

Lecture 9: Project Implementation Part 1: Numerical attribute analysis

Lecture 10: Project Implementation Part 2: categorical attribute analysis

Lecture 11: Project Implementation Part 3: Population comparations with box plot

Lecture 12: Project Implementation Part 4: Population comparations with bar plot

Lecture 13: Project 2 Implementation Part 1

Lecture 14: Project 2 Implementation Part 2

Lecture 15: Project 2 Implementation Part 3

Lecture 16: Project 2 Implementation Part 4

Lecture 17: Project 2 Implementation final Part

Chapter 3: Intermediate Visualization

Lecture 1: Advanced Scatter plot Part 1

Lecture 2: Advanced Scatter plot Part 2

Lecture 3: Advanced Scatter plot Part 3

Lecture 4: Advanced Scatter plot Part 4

Lecture 5: Advanced Scatter plot Part 5

Lecture 6: Advanced Scatter plot Final Part

Lecture 7: Advanced Bar Chart Part 1

Lecture 8: Advanced Bar Chart Part 2

Lecture 9: Advanced Heatmap

Lecture 10: Advanced combination of bar and heatmap

Lecture 11: Project 3: Practice bar plot, heatmap and circles

Chapter 4: Advanced Visualization

Lecture 1: Introduction to Plotly

Lecture 2: Basic plot with Plotly

Lecture 3: Project 4: Implementation Part 1

Lecture 4: Project 4: Implementation Part 2

Lecture 5: Project 4: Implementation Part 3

Lecture 6: Introduction to Another dimensions Part 1

Lecture 7: Introduction to Another dimensions Part 2

Lecture 8: Introduction to Another dimensions Part 3

Lecture 9: Introduction to Another dimensions Final Part

Lecture 10: (ONLY AVAILABLE IN THIS COURSE) other advanced plotting methods Part 1

Lecture 11: (ONLY AVAILABLE IN THIS COURSE) other advanced plotting methods Part 2

Lecture 12: (ONLY AVAILABLE IN THIS COURSE) other advanced plotting methods Part 3

Lecture 13: (ONLY AVAILABLE IN THIS COURSE) other advanced plotting methods Final Part

Chapter 5: Thank you

Lecture 1: Thank you

Instructors

Hoang Quy La
Electrical Engineer

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2 stars: 0 votes
3 stars: 1 votes
4 stars: 2 votes
5 stars: 3 votes

Frequently Asked Questions

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

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