biostats.joint_plot

biostats.joint_plot(data, x, y, color=None, kind='scatter')

Draw a combined plot to show the relation between two numeric variables.

Parameters:

datapandas.DataFrame

The input data. Must contain at least two numeric columns.

xstr

The numeric variable to be plotted in x-axis.

ystr

The numeric variable to be plotted in y-axis.

colorstr

The categorical variable specifying groups to be plotted with different colors. Maximum 20 groups. Optional.

kindstr

• “scatter” : Draw scatter plots.

• “regression” : Draw regression plots.

• “density” : Draw density plots.

• “histogram” : Draw histograms.

• “hexagon” : Draw hexagon plots.

Returns:

figmatplotlib.figure.Figure

The generated plot.

See also

ultimate_plot

Draw a multiple plot to show the relations between every two variables.

pair_plot

Draw a multiple plot to show the relations between every two numeric variables.

Examples

>>> import biostats as bs
>>> import matplotlib.pyplot as plt
>>> data = bs.dataset("penguins.csv")
>>> data
    species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  body_mass_g     sex
0    Adelie  Torgersen            39.1           18.7                181         3750    MALE
1    Adelie  Torgersen            39.5           17.4                186         3800  FEMALE
2    Adelie  Torgersen            40.3           18.0                195         3250  FEMALE
3    Adelie  Torgersen             NaN            NaN               <NA>         <NA>     NaN
4    Adelie  Torgersen            36.7           19.3                193         3450  FEMALE
..      ...        ...             ...            ...                ...          ...     ...
339  Gentoo     Biscoe             NaN            NaN               <NA>         <NA>     NaN
340  Gentoo     Biscoe            46.8           14.3                215         4850  FEMALE
341  Gentoo     Biscoe            50.4           15.7                222         5750    MALE
342  Gentoo     Biscoe            45.2           14.8                212         5200  FEMALE
343  Gentoo     Biscoe            49.9           16.1                213         5400    MALE

We want to visualize the relation between bill_length_mm and bill_depth_mm.

>>> fig = bs.joint_plot(data=data, x="bill_length_mm", y="bill_depth_mm", color="species", kind="scatter")
>>> plt.show()