heatmap

fcp.heatmap(**kwargs)

Heatmap plot.

Parameters

df (DataFrame) – DataFrame containing data to plot

Keyword Arguments

  • x (str) – x-axis column name [REQUIRED]

  • y (str) – y-axis column name [REQUIRED]

  • z (str) – z-axis column name [REQUIRED]

  • cell_size (int) – Width of a heatmap cell in pixels. Defaults to 60. More details

  • cmap (bool) – Name of a color map to apply to the plot. Defaults to inferno. More details

  • data_labels (bool) – Toggle visibility of value text labels on the heatmap cells. Defaults to False. More details

  • heatmap_edge_width (float) – Width of the edges of the heat map cells. Defaults to 0.

  • heatmap_font_color (str) – Hex color string for the value label text. Defaults to #ffffff .

  • heatmap_font_size (int) – Font size of the value label text. Defaults to 12.

  • heatmap_interp|interp (str) – imshow interpolation scheme [see matplotlib docs for more details]. Defaults to ‘none’.

  • cbar (bool) – Toggle colorbar on/off for contour and heatmap plots. Defaults to False. More details

  • size (int) – cbar width [height will match the height of the axes]. Defaults to 30.

Examples

Categorical heatmap:

>>> import fivecentplots as fcp
>>> from pathlib import Path
>>> import pandas as pd
>>> df = pd.read_csv(Path(fcp.__file__).parent / 'test_data/fake_data_heatmap.csv')
>>> fcp.heatmap(df, x='Category', y='Player', z='Average')
../_images/example_heatmap1.png

Non-uniform numerical data:

>>> import fivecentplots as fcp
>>> from pathlib import Path
>>> import pandas as pd
>>> df = pd.read_csv(Path(fcp.__file__).parent / 'test_data/fake_data_contour.csv')
>>> fcp.heatmap(df, x='X', y='Y', z='Value', row='Batch', col='Experiment',
                cbar=True, share_z=True, ax_size=[400, 400], data_labels=False,
                label_rc_font_size=12, filter='Batch==103', cmap='viridis')
../_images/example_heatmap2.png