String formatting code to use when adding annotations. annot_kws dict of key, value mappings, optional. Keyword arguments for matplotlib.axes.Axes.text() when annot is True. linewidths float, optional. Width of the lines that will divide each cell. linecolor color, optional. Color of the lines that will divide each cell. cbar bool, optional

Add colored labels to identify observations: lut = dict ( zip ( species . unique (), "rbg" )) row_colors = species . map ( lut ) sns . clustermap ( iris , row_colors = row_colors ) Use a different colormap and adjust the limits of the color range:

import seaborn as sns sns. set_theme (style = "whitegrid") # Load the brain networks dataset, select subset, and collapse the multi-index df = sns. load_dataset ("brain_networks", header = …

import pandas as pd import seaborn as sns sns. set_theme # Load the brain networks example dataset df = sns. load_dataset ("brain_networks", header = [0, 1, 2], index_col = 0) # Select a …

Annotated heatmaps#. seaborn components used: set_theme(), load_dataset(), heatmap()

String formatting code to use when adding annotations. annot_kws dict of key, value mappings, optional. Keyword arguments for matplotlib.axes.Axes.text() when annot is True. linewidths float, optional. Width of the lines that will divide each cell. linecolor color, optional. Color of the lines that will divide each cell. cbar bool, optional

Python source code: [download source: heatmap_annotation.py] import matplotlib.pyplot as plt import seaborn as sns sns . set () # Load the example flights dataset and convert to long-form flights_long = sns . load_dataset ( "flights" ) flights = flights_long . pivot ( "month" , "year" , "passengers" ) # Draw a heatmap with the numeric values in ...

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Variable in data to map plot aspects to different colors. hue_order list of strings. Order for the levels of the hue variable in the palette. palette dict or seaborn color palette. Set of colors for mapping the hue variable. If a dict, keys should be values in …

seaborn.FacetGrid.add_legend# FacetGrid. add_legend ( legend_data = None , title = None , label_order = None , adjust_subtitles = False , ** kwargs ) # Draw a legend, maybe placing it outside axes and resizing the figure.