biostats.pair_plot#
- biostats.pair_plot(data, variable, color=None, kind='scatter')[source]#
Draw a multiple plot to show the relations between every two numeric variables.
- Parameters:
- data
pandas.DataFrame
The input data. Must contain at least one numeric column.
- variable
list
The list of variables to be plotted.
- color
str
The categorical variable specifying groups to be plotted with different colors. Maximum 20 groups. Optional.
- kind
str
“scatter” : Draw scatter plots.
“regression” : Draw regression plots.
“density” : Draw density plots.
“histogram” : Draw histograms.
- data
- Returns:
- fig
matplotlib.figure.Figure
The generated plot.
- fig
See also
ultimate_plot
Draw a multiple plot to show the relations between every two variables.
joint_plot
Draw a combined plot to show the relation between 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 relations between these variables.
>>> fig = bs.pair_plot(data=data, variable=["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"], color="species", kind="scatter") >>> plt.show()