Box Plots#
We can generate box plots using .plot.box()
or .boxplot()
. The default settings visualize the distribution of values within each column.
Back to our random number DataFrame
, this time with five columns.
import pandas as pd, numpy as np # import statements
df = pd.DataFrame(np.random.randn(10, 5), columns=['A', 'B', 'C', 'D', 'E']) # create random data
df.plot.box() # box plot
<Axes: >

We can add colors to our box plot using the color
keyword.
df.plot.box(color='blue') # set color
<Axes: >

We can also use a dictionary with key-value pairs for each component of our box plot.
color = {"boxes": "DarkGreen", "whiskers": "DarkOrange", "medians": "DarkBlue", "caps": "Gray",} # color dictionary
df.plot.box(color=color, sym="r+") # draw plot and specify colors and outlier symbol using keyword argument or kwarg
<Axes: >

Additional Resources#
For more on box plots: