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Python 3 Pandas, Bokeh, and Seaborn Data Visualization

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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

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  • 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!

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