How to sync Colors across Subplots of different types

Question

I am trying to create a subplot with two plots. The first plot is essentially a scatter plot (i’m using regplot) and the second is a histogram.

my code is as follows:

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

data = {'source':['B1','B1','B1','C2','C2','C2'],
        'depth':[1,4,9,1,3,10],
        'value':[10,4,23,78,24,45]}

df = pd.DataFrame(data)

f, (ax1, ax2) = plt.subplots(1,2)

for source in df['source'].unique():
    
    x = df.loc[df['source'] == source, 'value']
    y = df.loc[df['source'] == source, 'depth']
    
    sns.regplot(x,
                y,
                scatter = True,
                fit_reg = False,
                label = source,
                ax = ax1)
    ax1.legend()
    
    sns.distplot(x,
                 bins = 'auto',
                 norm_hist =True,
                 kde = True,
                 rug = True,
                 ax = ax2,
                 label = source)
    ax2.legend()
    ax2.relim()
    ax2.autoscale_view()
plt.show()

The result is shown below.

As you can see, the colors between the scatter and the histogram are different. Now, I had a play around with color pallets and all, which has not worked. Can anyone shed any light on how I can sync the colors?

Asked By: BillyJo_rambler

||

Source

Answer 1

Use color argument of plotting functions. In this example from current seaborn color palette in your for cycle with itertools.cyclecolors to plot are selected one by one:

import pandas as pd 
import matplotlib.pyplot as plt 
import seaborn as sns 
import itertools
    
data = {'source':['B1','B1','B1','C2','C2','C2'],
        'depth':[1,4,9,1,3,10],
        'value':[10,4,23,78,24,45]}

df = pd.DataFrame(data)

f, (ax1, ax2) = plt.subplots(1,2)

# set palette 
palette = itertools.cycle(sns.color_palette())

# plotting 
for source in df['source'].unique():

    x = df.loc[df['source'] == source, 'value']
    y = df.loc[df['source'] == source, 'depth']

    # color
    c = next(palette)
    sns.regplot(x,
                y,
                scatter = True,
                fit_reg = False,
                label = source,
                ax = ax1,
                color=c)
    ax1.legend()

    sns.distplot(x,
                 bins = 'auto',
                 norm_hist =True,
                 kde = True,
                 rug = True,
                 ax = ax2,
                 label = source,
                 color=c)
    ax2.legend()
    ax2.relim()
    ax2.autoscale_view()

plt.show()

You can set your own color palette like in this answer

Answered By: Serenity

Answer 2

I had a very similar problem.

Here’s an alternative to Serenity’s answer (new parts w.r.t. original code highlighted):

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

data = {'source':['B1','B1','B1','C2','C2','C2'],
        'depth':[1,4,9,1,3,10],
        'value':[10,4,23,78,24,45]}

df = pd.DataFrame(data)

f, (ax1, ax2) = plt.subplots(1,2)

palette = sns.color_palette()
for color,source in zip(palette,df['source'].unique()):

      x = df.loc[df['source'] == source, 'value']
      y = df.loc[df['source'] == source, 'depth']

      sns.regplot(x,
                  y,
                  scatter = True,
                  fit_reg = False,
                  label = source,
                  ax = ax1,

                color=color)

      ax1.legend()

      sns.distplot(x,
                   bins = 'auto',
                   norm_hist =True,
                   kde = True,
                   rug = True,
                   ax = ax2,
                   label = source,

                 color=color)

      ax2.legend()
      ax2.relim()
      ax2.autoscale_view()
plt.show()

Basically, get the list of colors matplotlib is using with sns.color_palette().

Loop over the list of zip()-ped pairs (color, source), where color is in the list returned by sns.color_palette(), and specify color as a parameter in the call to sns.xxxplot().

Answered By: spenceryue

Answer 3

Make use of the hue_order parameter.

From seaborn documentation :
seaborn.countplot(*, x=None, y=None, hue=None, data=None, **order=None, hue_order=None,** orient=None, color=None, palette=None, saturation=0.75, dodge=True, ax=None, **kwargs)

order, hue_order: lists of strings, optional
Order to plot the categorical levels in, otherwise the levels are inferred from the data objects

hue_order = target_0['CODE_GENDER'].unique()

plt.subplot(2,2,1)
sns.countplot(x='INCOME_BRACKET', hue='GENDER',data = df_0,hue_order=hue_order,palette = 'mako')
plt.title("Non-defaulters : Income bracket b/w Gender - Target 0");

plt.subplot(2,2,2)
sns.countplot(x='INCOME_BRACKET', hue='GENDER',data = df_1,hue_order=hue_order,palette = 'mako')
plt.title("Defaulters : >Income bracket b/w Gender - Target 1");

Output as seen below :

Two subplots with synced colors

I realise this is an old question. However, this is quite simple(not sure if this was option was available before) which I couldn’t find in any of the other answers and these didn’t work for some reason too. So, this answer is for others who are still struggling with this.

Answered By: Sneha Valabailu

How to sync Colors across Subplots of different types

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