Conteúdo do Curso

Deep Dive into the seaborn Visualization

1. Light Start

Reading the File Colors

2. Distributions of Data

Histplot Kdeplot Rugplot Ecdfplot Challenge Displot

3. Categorical Plot Types

Stripplot Swarmplot Boxplot Violinplot Barplot Pointplot Challenge Catplot

4. Matrix Plots

Heatmap Clustermap

5. Multi-Plot Grids

FacetGrid PairGrid JointGrid

6. Regression Models

Regplot Lmplot

Deep Dive into the seaborn Visualization

Histplot

The distributions module contains several functions designed to answer questions such as these. The axes-level functions are histplot, kdeplot, ecdfplot, and rugplot. They are grouped together within the figure-level displot function.

A histplot is a classic visualization tool that represents the distribution of one or more variables by counting the number of observations that fall within discrete bins.

Click the slider to view possible arguments for the plot!

Don't forget to return back after exploring the dataset!

Note
Use plt.show() to display the plot.

Tarefa

Create the histplot using the seaborn library:

Set the x parameter equals the 'bill_length_mm';
Set the hue parameter equals the 'island';
Set the element parameter equals the 'step';
Set the stat parameter equals the 'density';
Set the binwidth parameter equals 1;
Set the 'flare' palette;
Use the df data for the plot;
Display the plot.

Tudo estava claro?

Seção 2. Capítulo 1

Conteúdo do Curso

Deep Dive into the seaborn Visualization

1. Light Start

Reading the File Colors

2. Distributions of Data

Histplot Kdeplot Rugplot Ecdfplot Challenge Displot

3. Categorical Plot Types

Stripplot Swarmplot Boxplot Violinplot Barplot Pointplot Challenge Catplot

4. Matrix Plots

Heatmap Clustermap

5. Multi-Plot Grids

FacetGrid PairGrid JointGrid

6. Regression Models

Regplot Lmplot

Deep Dive into the seaborn Visualization

Histplot

A histplot is a classic visualization tool that represents the distribution of one or more variables by counting the number of observations that fall within discrete bins.

Click the slider to view possible arguments for the plot!

Don't forget to return back after exploring the dataset!

Note
Use plt.show() to display the plot.

Tarefa

Create the histplot using the seaborn library:

Set the x parameter equals the 'bill_length_mm';
Set the hue parameter equals the 'island';
Set the element parameter equals the 'step';
Set the stat parameter equals the 'density';
Set the binwidth parameter equals 1;
Set the 'flare' palette;
Use the df data for the plot;
Display the plot.

Tudo estava claro?

Seção 2. Capítulo 1