dabl.plot
.discrete_scatter¶
-
dabl.plot.
discrete_scatter
(x, y, c, unique_c=None, legend='first', clip_outliers=True, alpha='auto', s='auto', ax=None, **kwargs)[source]¶ Scatter plot for categories.
Creates a scatter plot for x and y grouped by c.
- Parameters
- xarray-like
x coordinates to scatter.
- yarray-like
y coordinates to scatter.
- carray-like
Grouping of samples (similar to hue in seaborn).
- unique_carray-like, default=’None’
Unique values of c considered in scatter. If not provided unique elements of c are determined.
- legendbool, or “first”, default=”first”
Whether to create a legend. “first” mean only the first one in a given gridspec.
- clip_outliersbool, default=’True’
Whether to clip outliers in x and y. The limits are determined based on 0.01 and 0.99 quantiles of x and y ignoring nan values.
- alphafloat, default=’auto’
Alpha values for scatter plots. ‘auto’ is dirty hacks.
- sfloat, default=’auto’.
Marker size for scatter plots. ‘auto’ is dirty hacks.
- axmatplotlib axes, default=None
Axes to plot into.
- kwargs :
Passed through to plt.scatter.
Examples
>>> import matplotlib.pyplot as plt >>> from dabl.datasets import load_ames >>> data = load_ames() >>> fig = plt.figure() >>> discrete_scatter( ... x=data["Year Built"], ... y=data["SalePrice"], ... c=data["Overall Qual"], ... unique_c=[2, 4, 6, 8, 10], ... legend=True, ... alpha=0.3 ... )