Plotly library of Python can be very useful for data visualization and understanding the data simply and easily.
plotly.figure_factory.create_annotated_heatmap
Function that creates annotated heatmaps and adds annotations to each cell of the heatmap.
Syntax:plotly.figure_factory.create_annotated_heatmap(z, x=None, y=None, annotation_text=None, colorscale=’Plasma’, font_colors=None, showscale=False, reversescale=False, **kwargs)
Parameter:
z ((list[list]|ndarray)) – it describe the z matrix to create heatmap.
x ((list)) – it describe the x axis labels.
y ((list)) – it describe the y axis labels.annotation_text ((list[list]|ndarray)) – Text strings for annotations. Should have the same dimensions as the z matrix. If no text is added, the values of the z matrix are annotated. Default = z matrix values.
colorscale ((list|str)) – it describe heatmap colorscale.
font_colors ((list)) – it describes the list of two color strings: [min_text_color, max_text_color]
showscale ((bool)) – it display colorscale with Default as False
reversescale ((bool)) – it reverse colorscale with Default as False
Example 1: Simple annotated heatmap with default configuration
Python3
import plotly.figure_factory as ff
z = [[0.300000, 0.00000, 0.65, 0.300000],
[1, 0.100005, 0.45, 0.4300],
[0.300000, 0.00000, 0.65, 0.300000],
[1, 0.100005, 0.45, 0.00000]]
fig = ff.create_annotated_heatmap(z)
fig.show()
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Output:
Example 2: Defined colorscale
Python3
import plotly.figure_factory as ff
z = [[.1, .3, .5, .7],
[1, .8, .6, .4],
[.6, .4, .2, .0],
[.9, .7, .5, .3]]
fig = ff.create_annotated_heatmap(z, colorscale='Viridis')
fig.show()
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Output:
