DataCamp – [PYTHON] Data Visualization with SeaBorn

DataCamp – [ PYTHON ] Data Visualization with SeaBorn
English | Size: 400.39 MB
Category: Tutorial

DATA VISUALIZATION WITH SEABORN

PROGRAMMING – LANGUAGE : Python

FORMAT: .mp4, .pdf

COURSES COUNT: 2

DURATION : 8 Hours(4 + 4)

TONGUE: English

—————————————————– C O N T E N T ————————————————

1. Introduction to Data Visualization with Seaborn

Course Description
Seaborn is a powerful Python library that makes it easy to create informative and attractive visualizations. This course provides an introduction to Seaborn and teaches you how to visualize your data using plots such as scatter plots, box plots, and bar plots. You’ll do this while exploring survey responses about student hobbies and the factors that are associated with academic success. You’ll also learn about some of Seaborn’s advantages as a statistical visualization tool, such as how it automatically calculates confidence intervals. By the end of the course, you will be able to use Seaborn in a variety of situations to explore your data and effectively communicate the results of your data analyses to others.

CHAPTER DETAILS

1. Introduction to Seaborn

2. Visualizing Two Quantitative Variables

3. Visualizing a Categorical and a Quantitative Variable

4. Customizing Seaborn Plots

2. Intermediate Data Visualization with Seaborn

Course Description
Do you want to make beautiful, informative visualizations with ease? If so, then you must learn seaborn! Seaborn is a visualization library that is an essential part of the python data science toolkit. In this course, you will learn how to use seaborn’s sophisticated visualization tools to analyze multiple real world datasets including the American Housing Survey, college tuition data, and guests from the popular television series, The Daily Show. Following this course, you will be able to use seaborn functions to visualize your data in several different formats and customize seaborn plots for your unique needs.

CHAPTER DETAILS

1. Seaborn Introduction

2. Customizing Seaborn Plots

3. Additional Plot Types

4. Creating Plots on Data Aware Grids

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