switch color of one given bar in a bar plot of a pandas dataframe in python

Question

I have the following barh plot of a given dataframe:

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

df = pd.DataFrame({"first":np.arange(1,6), "second":np.arange(2,7)}) 
df.plot(kind="barh", color=tuple(["g", "b"]))

image of df plot

I want to switch to a custom color, namely "#af12be22", the bar that corresponds to df.loc[0,"a"], that is the shortest green bar.

Idealy I would like to have a simple way to control for colors of each of the cells, say by giving a dataframe as the argument of the "color" parameter of the .plot method. Something like:

df = pd.DataFrame({"first":np.arange(1,6), "second":np.arange(2,7)}) 
df_colors = pd.DataFrame({"first":["#af12be22"] + 4*["g"], "second":5*["b"]})  
df.plot(kind="barh", color=df_color)

Is it possible ?

I looked at the pandas.DataFrame.plot documentation and saw that "color" seemed to only allow color variation from a column of a dataframe to another, but not within a column. I tried to change the df_color into an np.array or a list, but did not help either, with the following error message:

ValueError: Invalid color ['#af12be22' 'g' 'g' 'g' 'g']

I do understand the error, but would tike to know if there is an easy workaround

Redox · Accepted Answer · 2023-01-24 16:09:33Z

1

The below change (updated code)

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

df = pd.DataFrame({"first":np.arange(1,6), "second":np.arange(2,7)}) 
df.plot(kind="barh", color={"first":["#af12be22"] + 4*["g"], "second":5*["b"]})

will give you what I think you are looking for. Hope this helps.

answered Jan 24, 2023 at 16:09

Redox

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3 Comments

Victor Daniel Over a year ago

Great, many thanks! Exactly what I want

mosc9575 Over a year ago

@VictorDaniel Please click the check mark below the voting error. This is how you give credit to the author of the answer. And it also shows, that the problem is solved. This can save other people some time.

Victor Daniel Over a year ago

Yep yep, didn't know this feature existed

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