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ALLCools.plot.categorical_scatter

ALLCools.plot.categorical_scatter

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categorical_scatter(data, ax, coord_base='umap', x=None, y=None, hue=None, palette='auto', text_anno=None, text_anno_kws=None, text_anno_palette=None, text_transform=None, dodge_text=False, dodge_kws=None, show_legend=False, legend_kws=None, s=5, size=None, sizes: dict = None, size_norm=None, axis_format='tiny', max_points=5000, labelsize=4, linewidth=0, zoomxy=1.05, outline=None, outline_pad=3, outline_kws=None, scatter_kws=None, return_fig=False, rasterized='auto')[source]
Plot scatter plot with these options:

  • Color by a categorical variable, and generate legend of the variable if needed

  • Add text annotation using a categorical variable

  • Circle categories with outlines

Parameters

  • data – Dataframe that contains coordinates and categorical variables

  • ax – this function do not generate ax, must provide an ax

  • coord_base – coords name, if provided, will automatically search for x and y

  • x – x coord name

  • y – y coord name

  • hue – categorical col name or series for color hue

  • palette – palette of the hue, str or dict

  • text_anno – categorical col name or series for text annotation

  • text_anno_kws –

  • text_anno_palette –

  • text_transform –

  • dodge_text –

  • dodge_kws –

  • show_legend –

  • legend_kws –

  • s –

  • size –

  • sizes –

  • size_norm –

  • axis_format –

  • max_points –

  • labelsize –

  • linewidth –

  • zoomxy –

  • outline –

  • outline_pad –

  • outline_kws –

  • scatter_kws – kws dict pass to sns.scatterplot

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