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Corso

Intermediate Data Visualization with Seaborn

IntermedioLivello di competenza

Aggiornato 05/2026

Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.

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PythonData Visualization

4 h

13 video

50 Esercizi

4,200 XP

75,054

Attestato di conseguimento

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Descrizione del corso

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.

Prerequisiti

Data Manipulation with pandas

1

Seaborn Introduction

Introduction to the Seaborn library and where it fits in the Python visualization landscape.

Introduction to Seaborn

Seaborn foundation

Reading a csv file

Comparing a histogram and displot

Using the distribution plot

Plot a histogram

Rug plot and kde shading

Interpreting the results

Regression Plots in Seaborn

Create a regression plot

Plotting multiple variables

Facetting multiple regressions

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2

Customizing Seaborn Plots

Overview of functions for customizing the display of Seaborn plots.

Using Seaborn Styles

Setting the default style

Comparing styles

Removing spines

Colors in Seaborn

Matplotlib color codes

Using default palettes

Color Palettes

Creating Custom Palettes

Customizing with matplotlib

Using matplotlib axes

Additional plot customizations

Adding annotations

Multiple plots

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3

Additional Plot Types

Overview of more complex plot types included in Seaborn.

Categorical Plot Types

stripplot() and swarmplot()

boxplots, violinplots and boxenplots

barplots, pointplots and countplots

Regression Plots

Regression and residual plots

Regression plot parameters

Binning data

Matrix plots

Creating heatmaps

Customizing heatmaps

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4

Creating Plots on Data Aware Grids

Using Seaborn to draw multiple plots in a single figure.

Using FacetGrid, catplot and lmplot

Building a FacetGrid

Using a catplot

Using a lmplot

Using PairGrid and pairplot

Building a PairGrid

Using a pairplot

Additional pairplots

Using JointGrid and jointplot

Building a JointGrid and jointplot

Jointplots and regression

Complex jointplots

Selecting Seaborn Plots

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Intermediate Data Visualization with Seaborn

Corso
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