Conditional Formatting Within a Pandas DataFrame in Jupyter

Question

I have an arbitrary dataframe, something like this:

import pandas as pd
df = pd.DataFrame.from_dict({'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd'], 'col_3':[100,-100, 50, -50,]})
df

is there a way to change the formatting for each item in such a way that larger values within a column are one color and smaller values are another? Preferably the implementation would be:

something brief
able to be applied to most simple dataframes
robust enough to handle different datatypes

as an example, Excel has conditional formatting which looks like this:

It doesn't do anything meaningful with strings or chars, but otherwise behaves nicely

https://stackoverflow.com/questions/28075699/coloring-cells-in-pandas — BENY, Sep 08 '20 at 00:50

score 1 · Accepted Answer · answered Sep 08 '20 at 01:18

Like many amazing things, you can do it with seaborn

this:

import pandas as pd
df = pd.DataFrame.from_dict({'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd'], 'col_3':[100,-100, 50, -50,]})

import seaborn as sns
cm = sns.light_palette("green", as_cmap=True)
s = df.style.background_gradient(cmap=cm)
s

makes this:

Conditional Formatting Within a Pandas DataFrame in Jupyter

1 Answers1