Data Visualization in Python Using Seaborn Library
Learn how to analyze and create amazing data visualizations with Python!
Development ,Programming Languages,Python
Lectures -20
Resources -1
Duration -2 hours
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Course Description
Welcome to Mastering Data Visualization! In this course, you're going to learn about the Theory and Foundations of Data Visualization so that you can create amazing charts that are informative, true to the data, and communicatively effective.
"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.
This course is designed to teach analysts, students interested in data science, statisticians, and data scientists how to analyze real-world data by creating professional-looking charts and using numerical descriptive statistics techniques in Python 3.
We'll teach you how to program with Python, and how to analyze and create amazing data visualizations with Python! You can use this course as your ready-to-go reference for your own project.
Who is this course for?
Programmers / Researchers / Designers who want to learn how to produce top-quality plots.
Anyone who has to present data at some point!
Data Scientists.
Academic scientists have to publish in scientific journals.
Journalists / Data Journalists.
Communication experts.
Also the general public: you should know how graphs work because they're everywhere!
What will you learn in this course?
Describe what makes a good or bad visualization.
Understand best practices for creating basic charts.
Identify the functions that are best for particular problems.
Create a visualization seaborn.
Distribution Plot.
Histograms.
KDE Plots.
Scatter Plot.
Rug Plot.
Joint Plot.
Pair Plot.
Bar Plot.
Count Plot.
Box Plot.
Violin Plot.
Strip Plot.
Swarm Plot
Heat Map.
Pair Plot.
Sub Plot.
Skills you will gain:
Python Programming.
Data Virtualization.
Data Visualization (DataViz).
seaborn.
If you need to analyze, present or communicate data professionally at some point, this course is a must.
I really encourage you to deepen your knowledge of Data Visualization. It's not a difficult topic, and we will start from the basics. You don't need any previous knowledge. I'll teach you everything you need to know along the way and we'll go straight to the point. No rambling. I really hope to see you in class!
Goals
- What is Data Visualization?
- Why Should you use Data Visualization in Analytics and Business Intelligence projects?
- Data Visualization in Python.
- Seaborn Library.
- Distribution Plot, Histograms, KDE Plots, Scatter Plot, Rug Plot, Joint Plot, Pair Plot, Bar Plot, Count Plot, Box Plot, Violin Plot, Strip Plot, Swarm Plot, Heat Map, Pair Plot, Sub Plot.
Prerequisites
- No introductory skill level in Python programming is required.
- Desire to learn!

Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
2 Lectures
-
Introduction 03:32 03:32
-
Importing the data 06:29 06:29
Distribution Plot
2 Lectures

KDE Plot
3 Lectures

Scatter Plot
1 Lectures

Rug Plot
1 Lectures

Joint Plot
1 Lectures

Pair Plot
1 Lectures

Bar Plot
1 Lectures

Count Plot
1 Lectures

Box Plot
1 Lectures

Violin Plot
1 Lectures

Strip Plot
1 Lectures

Swarm Plot
1 Lectures

Heat Map
1 Lectures

Pair Grid
1 Lectures

Sub Plots
1 Lectures

Instructor Details

ADITYA
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