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pythonpandasdataframematplotlibbar-chart
Victor Daniel
Victor Daniel

Reputation: 25

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

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

Upvotes: 1

Views: 102

Answers (1)

Redox
Redox

Reputation: 9967

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.

enter image description here

Upvotes: 1

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