In [3]:
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="white", context="talk")
rs = np.random.RandomState(7)
In [4]:
%matplotlib inline
In [5]:
# Set up the matplotlib figure
f, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(8, 6), sharex=True)
# Generate some sequential data
x = np.array(list("ABCDEFGHI"))
y1 = np.arange(1, 10)
sns.barplot(x, y1, palette="BuGn_d", ax=ax1)
ax1.set_ylabel("Sequential")
# Center the data to make it diverging
y2 = y1 - 5
sns.barplot(x, y2, palette="RdBu_r", ax=ax2)
ax2.set_ylabel("Diverging")
# Randomly reorder the data to make it qualitative
y3 = rs.choice(y1, 9, replace=False)
sns.barplot(x, y3, palette="Set3", ax=ax3)
ax3.set_ylabel("Qualitative")
Out[5]:
In [ ]: