I\'m using seaborn
and pandas
to create some bar plots from different (but related) data. The two datasets share a common category used as a hue<
The easiest solution to make sure to have the same colors for the same categories in both plots would be to manually specify the colors at plot creation.
# First bar plot
ax = sns.barplot(data=a, x='Scenario', y='Duration',
hue='Program', ci=None, palette=["C0", "C1", "k"])
# ...
# Second bar plot
ax2 = sns.barplot(data=b, x='Scenario', y='Duration',
hue='Program', ci=None, palette=["C0", "C1", "C2", "k"])
The color "C2"
(the third color of the color cycle) is only present in the second plot where there exists a Programm C.
Instead of a list, you may also use a dictionary, mapping values from the hue
column to colors.
palette ={"A": "C0", "B": "C1", "C": "C2", "Total": "k"}
ax = sns.barplot(data=a, x='Scenario', y='Duration', hue='Program', palette=palette)
# ...
ax2 = sns.barplot(data=b, x='Scenario', y='Duration', hue='Program', palette=palette)
In both cases, the output would look like this:
Finally, you may create this dictionary automatically from the values from the hue
column. The advantage here would be that you neither need to know the colors, nor the values in the respective dataframes beforehands.
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
sns.set_style('darkgrid')
fig, ax = plt.subplots()
a = pd.DataFrame({'Program': ['A', 'A', 'B', 'B', 'Total', 'Total'],
'Scenario': ['X', 'Y', 'X', 'Y', 'X', 'Y'],
'Duration': [4, 3, 5, 4, 9, 7]})
b = pd.DataFrame({'Program': ['A', 'A', 'B', 'B', 'C', 'C', 'Total', 'Total'],
'Scenario': ['X', 'Y', 'X', 'Y', 'X', 'Y', 'X', 'Y'],
'Duration': [4, 3, 5, 4, 3, 2, 12, 9]})
unique = a["Program"].append(b["Program"]).unique()
palette = dict(zip(unique, sns.color_palette(n_colors=len(unique))))
palette.update({"Total":"k"})
ax = sns.barplot(data=a, x='Scenario', y='Duration',
hue='Program', ci=None, palette=palette)
plt.tight_layout()
plt.figure()
ax2 = sns.barplot(data=b, x='Scenario', y='Duration',
hue='Program', ci=None, palette=palette)
plt.tight_layout()
plt.show()