HoloViews: create boxplots for every column in a pandas dataframe

Question

I'm able to create the following boxplot with Pandas pandas.DataFrame.boxplot() method:

import pandas as pd
import numpy as np

np.random.seed(1234)
df = pd.DataFrame(np.random.rand(10, 4),
                  columns=['Col1', 'Col2', 'Col3', 'Col4'])

df.plot.box()
plt.show()

Although, if I try to do the same using HoloViews' BoxWhisker Element with Bokeh as backend, it works fine for a single column:

import holoviews as hv
from holoviews import opts
hv.extension('bokeh')

hv.BoxWhisker(
    data=df['Col1'],
    vdims='Col1'
)

But as soon as I try to add just another column, I get the below error:

hv.BoxWhisker(
    data=df[['Col1', 'Col2']]
)

DataError: None of the available storage backends were able to support the supplied data format. PandasInterface raised following error:

 unsupported operand type(s) for +: 'NoneType' and 'int'

PandasInterface expects tabular data, for more information on supported datatypes see http://holoviews.org/user_guide/Tabular_Datasets.html

I can't understand whether there is a problem with the Tabular Data HoloViews understands, or I'm not able to apply the syntaxis properly.

Answer 1

I would also recommend James Bednar's answer, which is using hvPlot. HvPlot is built on top of HoloViews:

import hvplot.pandas
df.hvplot.box()

However, if you want to do it in HoloViews instead of hvPlot, you would have to melt your data to get all column names in one column, and all values in the other column.

This code works for your sample data:

hv.BoxWhisker(df.melt(), kdims='variable', vdims='value')

Answer 2

I'm not sure how to achieve what you want from the native HoloViews BoxWhisker interface, which is set up for tidy data rather than a set of independent columns like that. Meanwhile you can use hvPlot just as you use the native .plot() call: