How to change the color of matplotlib AxisSubplot?

Question

I was wondering how to change the color of matplotlib AxisSubplot object.

Here is the MWE:

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


df = sns.load_dataset('iris')


p = df.hist('sepal_length',by='species',layout=(3,1))
p[0].set(title='Changed')
p[0].set(facecolor='b')

plt.tight_layout()
plt.show()

Type

print(type(p[0])
matplotlib.axes._subplots.AxesSubplot

My output

Required

I want the color of histogram to be blue, not the background.

p[0] ==> red
p[1] ==> green
p[2] ==> blue
something like
p[0].set_color('r')
p[1].set_color('g')
p[2].set_color('b')

Answer 1

You can try this:

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


df = sns.load_dataset('iris')

n_unq = df['species'].nunique()
colors = (list('rgbcmyk')*100)[:n_unq]

xmin = np.min(df['sepal_length'])
xmax = np.max(df['sepal_length'])

fig, ax = plt.subplots(n_unq,1,figsize=(12,8))

for i, (label,grp) in enumerate(df.groupby('species')):
    series = grp['sepal_length']
    p = series.hist(ax=ax[i],color=colors[i],label=label)
    p.set(xlim=(xmin, xmax))
    p.legend()

plt.tight_layout()
plt.show()

Gives:

Answer 2

I've done it using seaborn's distplot, first i've found unique strings in the species column, for each of them, i draw a distinct histogram in each subplot based on sepal_length. as you can see i set the color of first histogram to be Blue, and the remaining plots are Red !

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


df = sns.load_dataset('iris')

unique_species = np.unique(df['species'])
for i in range(len(unique_species)):
    plt.subplot(1,len(unique_species),i+1)
    temp = df.loc[np.where(df['species']==unique_species[i])]
    if i == 0 :
        sns.distplot(temp['sepal_length'],bins=10,kde=False,rug=False,color='b')
    else:
        sns.distplot(temp['sepal_length'],bins=10,kde=False,rug=False,color='r')
    plt.title(unique_species[i])
plt.show()

the resulting plot would be :