seaborn the DataFrame Plotting Library for Python (Spyder 5 IDE)

This guide will look at the use of seaborn, which is a wrapper around the matplotlib plotting library optimised for the pandas dataframe data structure. seaborn includes functions to set a consistent style and palette across plots.

The seaborn plotting library includes a number of plotting functions. seaborn splits data in dataframes using categories in categorical series to give multiple lines for example in a line plot. These categorical series can be assigned to the keyword input argument hue in the seaborn plotting functions.

Some seaborn plotting functions operate on the axes level, manipulating the currently selected matplotlib axes which is the form of a matplotlib AxesSubplot. Other seaborn plotting functions operate directly on the figure level, where they essentially create a new figure and this new figure can contain one or multiple AxesSubplots. These figures are usually instances of seaborn classes such as the FacetGrid, AxisGrid or ClusterGrid.

Before getting started with seaborn you should be comfortable with the Python programming language, numpy, pandas and matplotlib. The dataframe data structure will be used to store the data that is to be plotted.

Written Guides:
https://dellwindowsreinstallationguide.com/python/
Python Playlist:
https://www.youtube.com/playlist?list=PL1RkaknDn7v-EO4V38oDBkZNd6_530nan

0:01:00 matplotlib Recap
0:02:08 Styles
0:03:48 Color Palettes
0:12:44 pandas Recap and Example Datasets
0:21:50 seaborn Modules
0:22:35 Relational Plots (lineplot and scatterplot Axes Level AxesSubplot)
0:23:56 Hue
0:26:45 Accessing matplotlib Figure and AxesSubplots from a Seaborn Axes Level Seaborn Plot (AxesSubplot)
0:28:28 Relational Plots (relplot Figure Level FacetGrid)
0:30:12 FacetGrid keyword input arguments (col, row, col_wrap and kind)
0:32:02 Accessing matplotlib Figure and AxesSubplots from a Seaborn Figure Level Seaborn Plot (FacetGrid)
0:33:08 Regression Plots (regplot and residplot Axes Level AxesSubplot)
0:35:59 numpy Polynomial Fit
0:38:33 Regression Plots (lmplot Figure Level FacetGrid)
0:43:31 Distribution Plots (rugplot, histplot, kdeplot and ecdfplot Axes Level AxesSubplot)
0:54:12 Distribution Plots (displot Figure Level FacetGrid)
0:57:20 AxisGrid Plots (jointplot and pairplot Figure Level AxisGrid)
1:01:32 Categorical Plots (boxplot, violinplot, barplot, pointplot, stripplot streamplot, countplot Axes Level AxesSubplot)
1:05:06 Categorical Plots (catplot Figure Level FacetGrid)
1:06:12 Matrix Plots (heatmap Axes Level AxesSubplot)
1:09:20 Matrix Plots (clustermap Figure Level ClusterGrid)
#seaborn #spyder #python