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Python 3 Pandas, Bokeh, and Seaborn Data Visualization

  • Development
  • May 08, 2025
SynopsisPython 3 Pandas, Bokeh, and Seaborn Data Visualization, avail...
Python 3 Pandas, Bokeh, and Seaborn Data Visualization  No.1

Python 3 Pandas, Bokeh, and Seaborn Data Visualization, available at $19.99, has an average rating of 4.1, with 73 lectures, based on 16 reviews, and has 1102 subscribers.

You will learn about Prepare Awesome Visualizations Publications and Printing quality Visualizations 3D Visualizations Add Matplotlib, NumPy, seaborn, and bokeh in resume Appear for Data Science interviews confidently This course is ideal for individuals who are Data Scientists, Data Analysts, and Data Engineers or Mathematicians, Statisticians, Scientists, and Engineers or Machine Learning and AI Professionals or Bioinformatics and Biostatistics professionals or Programmers and Developers or Students, Job seekers, anyone wanting to learn new stuff It is particularly useful for Data Scientists, Data Analysts, and Data Engineers or Mathematicians, Statisticians, Scientists, and Engineers or Machine Learning and AI Professionals or Bioinformatics and Biostatistics professionals or Programmers and Developers or Students, Job seekers, anyone wanting to learn new stuff.

Enroll now: Python 3 Pandas, Bokeh, and Seaborn Data Visualization

Summary

Title: Python 3 Pandas, Bokeh, and Seaborn Data Visualization

Price: $19.99

Average Rating: 4.1

Number of Lectures: 73

Number of Published Lectures: 73

Number of Curriculum Items: 73

Number of Published Curriculum Objects: 73

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • Prepare Awesome Visualizations
  • Publications and Printing quality Visualizations
  • 3D Visualizations
  • Add Matplotlib, NumPy, seaborn, and bokeh in resume
  • Appear for Data Science interviews confidently
  • Who Should Attend

  • Data Scientists, Data Analysts, and Data Engineers
  • Mathematicians, Statisticians, Scientists, and Engineers
  • Machine Learning and AI Professionals
  • Bioinformatics and Biostatistics professionals
  • Programmers and Developers
  • Students, Job seekers, anyone wanting to learn new stuff
  • Target Audiences

  • Data Scientists, Data Analysts, and Data Engineers
  • Mathematicians, Statisticians, Scientists, and Engineers
  • Machine Learning and AI Professionals
  • Bioinformatics and Biostatistics professionals
  • Programmers and Developers
  • Students, Job seekers, anyone wanting to learn new stuff
  • Become a Master in Advanced Data Visualization with Python 3 and acquire employers’ one of the most requested skills of 21st Century! A great data engineer/scientist earns more than $150000 per year in today’s market!

    This is the most comprehensive, yet straight-forward course for the Advanced Data Visualization with Python 3 on Udemy! Whether you have never worked with Data Visualization before, already know basics of Python, or want to learn the advanced features of matplotlib and seaborn with Python 3, this course is for you! In this course we will teach you Advanced Data Visualization with Python 3, Jupyter, NumPy, Matplotlib, seaborn, pandas, and Bokeh. 

    (Note, we also provide you PDFs and Jupyter Notebooks in case you need them)

    With over 70 lectures and more than 9 hours of video this comprehensive course leaves no stone unturned in teaching you Data Visualization with Python 3!

    This course will teach you Data Visualization in a very practical manner, with every lecture comes a full programming video and a corresponding Jupyter notebook that has Python 3 code! Learn in whatever manner is the best for you!

    We will start by helping you get Python3, NumPy, matplotlib, and Jupyter installed on your Windows computer and Raspberry Pi.

    We cover a wide variety of topics, including:

  • Basics of Scientific Python Ecosystem

  • Basics of Digital Image Processing

  • Basics of NumPy and Matplotlib

  • Installation of Python 3 on Windows

  • Setting up Raspberry Pi

  • Tour of Python 3 environment on Raspberry Pi

  • Jupyter installation and basics

  • NumPy Ndarrays

  • Array Creation Routines

  • Basic Visualization with Matplotlib

  • Ndarray Manipulation

  • Random Array Generation

  • Bitwise Operations

  • Statistical Functions

  • Plotting with Matplotlib

  • Python 3 and Matplotlib Data Visualization Recipes

  • Seaborn recipes

  • Seaborn and Pandas

  • Bokeh

  • and much more.

  • You will get lifetime access to over 70 lectures plus corresponding PDFs and the Jupyter notebooks for the lectures! 

    So what are you waiting for? Learn Data Visualization with Python 3 in a way that will advance your career and increase your knowledge, all in a fun and practical way!

    Course Curriculum

    Chapter 1: Introduction to the course

    Lecture 1: Objectives

    Lecture 2: Topics Overview

    Lecture 3: Introduction to the Scientific Python Ecosystem

    Lecture 4: Please do leave your feedback

    Chapter 2: Python 3 on Windows Computer

    Lecture 1: Install Python 3 on Windows

    Lecture 2: Verify Python 3 environment on Windows

    Chapter 3: Python 3 on Raspberry Pi

    Lecture 1: What is Raspberry Pi?

    Lecture 2: Raspberry Pi OS Setup

    Lecture 3: Remote Connection to Raspbian Desktop with VNC

    Lecture 4: Install IDLE3 on Raspbian

    Lecture 5: Python 3 on Raspberry Pi

    Lecture 6: Additional Software for Remote Connection

    Lecture 7: Turn your Raspberry Pi 4 into a portable Tablet with Sunfounder Raspad 3

    Chapter 4: Python 3 Basics

    Lecture 1: Hello World on Windows

    Lecture 2: Hello World on Raspberry Pi

    Lecture 3: Interpreter vs Script

    Lecture 4: A brief Tour of IDLE

    Lecture 5: Raspberry Pi Vs PC

    Chapter 5: Python Package Index and pip

    Lecture 1: PyPI and pip

    Lecture 2: pip on Windows

    Lecture 3: pip on Raspberry Pi

    Chapter 6: Installing NumPy and Matplotlib

    Lecture 1: Install Matplotlib and NumPy on Windows

    Lecture 2: Install Matplotlib and NumPy on Raspberry Pi

    Chapter 7: Jupyter Notebook

    Lecture 1: Jupyter and IPython

    Lecture 2: Jupyter Installation on Windows

    Lecture 3: Jupyter Installation on Raspberry Pi

    Lecture 4: PuTTY

    Lecture 5: Connecting to a remote Jupyter Notebook

    Lecture 6: A brief tour of Jupyter

    Lecture 7: Jupyter Notebook Notes

    Chapter 8: Getting Started with NumPy

    Lecture 1: Introduction to NumPy

    Lecture 2: Ndarrays Indexing and Slicing

    Lecture 3: Ndarray Properties

    Lecture 4: NumPy Constants

    Lecture 5: NumPy Data Types

    Chapter 9: Creation of Arrays and Matplotlib

    Lecture 1: Ones and Zeros

    Lecture 2: Matrices

    Lecture 3: Introduction to Matplotlib

    Lecture 4: Numerical Ranges and Visualization

    Chapter 10: Random Sampling

    Lecture 1: Random Sampling

    Chapter 11: Array Manipulation

    Lecture 1: Array Manipulation

    Chapter 12: Bitwise Operations

    Lecture 1: Bitwise Operations

    Chapter 13: Statistical Functions

    Lecture 1: Statistical Functions

    Chapter 14: Pandas

    Lecture 1: What is Pandas?

    Lecture 2: Install Pandas on Raspberry Pi

    Lecture 3: Install Pandas on Windows

    Lecture 4: Series

    Lecture 5: DataFrame

    Chapter 15: Pandas Visualizations

    Lecture 1: Pandas Visualizations Part 1

    Lecture 2: Pandas Visualizations Part 2

    Lecture 3: Pandas Visualizations Part 3

    Chapter 16: Seaborn

    Lecture 1: Pandas Datasets in Seaborn

    Lecture 2: Colors and Asthetics

    Lecture 3: Visualizations and Plots

    Lecture 4: Visualizing Regression in seaborn

    Lecture 5: Uni-variate Data Visualization

    Lecture 6: Catplot

    Lecture 7: Pairgrid

    Chapter 17: Visualizations in Bokeh

    Lecture 1: Getting Started with Bokeh

    Lecture 2: More Bokeh

    Lecture 3: Layouts in Bokeh

    Lecture 4: Column Data Source

    Lecture 5: Column Data Source Visualizations

    Lecture 6: Log Axis Example

    Lecture 7: Scatter Plot

    Lecture 8: Brushes

    Lecture 9: Stock Price Visualization

    Lecture 10: Interactive graph within Notebook

    Lecture 11: Interactive Visualization

    Lecture 12: Bullet Graphs

    Chapter 18: A complete data Science example

    Lecture 1: A complete data Science example

    Chapter 19: Downloadable Code Files

    Lecture 1: Downloadbale Code Bundle

    Chapter 20: BONUS SECTION

    Lecture 1: BONUS LECTURE

    Instructors

  • Python 3 Pandas, Bokeh, and Seaborn Data Visualization  No.2
    Ashwin Pajankar ? 85,000+ Students Worldwide
    Instructor | Programmer | Maker | Author | Youtuber
  • Rating Distribution

  • 1 stars: 0 votes
  • 2 stars: 2 votes
  • 3 stars: 0 votes
  • 4 stars: 3 votes
  • 5 stars: 11 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!