CODEWITHSUNDEEP
pythonpython-3.xmatplotlibseaborn
user3725021
user3725021

Reputation: 606

Create a 2x2 grid of python seaborn heatmaps with shared axes

I am looking to create a 2 x 2 grid of seaborn heatmaps from a pandas dataframe in python, but I am having trouble getting the desired result. Currently, this code...

import numpy as np
import pandas as pd
import seaborn as sns

df = pd.DataFrame({'x': np.random.uniform(0, 100, 1000), 
                   'y': np.random.uniform(0, 100, 1000), 
                   'z1': np.random.uniform(0, 1, 1000),
                   'z2': np.random.uniform(0, 1, 1000),
                   'z3': np.random.uniform(0, 1, 1000),
                   'z4': np.random.uniform(0, 1, 1000)})

fig,axn = plt.subplots(2, 2, sharex=True, sharey=True)
result0 = df.pivot(index='x', columns='y', values='z1')
result1 = df.pivot(index='x', columns='y', values='z2')
result2 = df.pivot(index='x', columns='y', values='z3')
result3 = df.pivot(index='x', columns='y', values='z4')

plt.subplot(2, 2, 1)
sns.heatmap(result0, annot=False, cmap='RdBu_r')
plt.subplot(2, 2, 2)
sns.heatmap(result1, annot=False, cmap='RdBu_r')
plt.subplot(2, 2, 3)
sns.heatmap(result2, annot=False, cmap='RdBu_r')        
plt.subplot(2, 2, 4)
sns.heatmap(result3, annot=False, cmap='RdBu_r')

generates a graph that looks like this... enter image description here

But the features I want to add are:

That sample data doesn't really do the heatmap justice, but I couldn't figure out a better way atm. Any help solving five points above would be greatly appreciated. Thanks!

Upvotes: 2

Views: 4906

Answers (2)

chthonicdaemon
chthonicdaemon

Reputation: 19770

For the data that you have here, hexbin makes more sense that heatmap. This solution uses ImageGrid to handle most of the requirements quite naturally. Note that I'm passing specific values for max and min so that the colorbar works correctly.

from mpl_toolkits.axes_grid1 import ImageGrid

fig = plt.figure()
grid = ImageGrid(fig, 111, nrows_ncols=(2, 2), axes_pad=0.3, cbar_mode='single')

for ax, col in zip(grid, ['z1', 'z2', 'z3', 'z4']):
    hb = ax.hexbin(df.x, df.y, C=df[col], cmap='RdBu_r', vmin=0, vmax=1)
    ax.set_title(col)
    ax.set_xlabel('x')
    ax.set_ylabel('y')

grid.cbar_axes[0].colorbar(hb)

sample hexbin

Upvotes: 1

phi
phi

Reputation: 11704

You can play with xticklabels, yticklabels, cbar parameters.

fig,axn = plt.subplots(2, 2, sharex=True, sharey=True, figsize=(6, 6))
xticks = ['{0:.0%}'.format(i/1000) if i % 100 == 0 else '' for i in range(1000)]
yticks = ['{0:.0%}'.format(i/1000) if i % 100 == 0 else '' for i in range(999, 0, -1)]
ax = plt.subplot(2, 2, 1)
cbar_ax = fig.add_axes([.91, .3, .03, .4])

sns.heatmap(
    result0.iloc[-1::-1, -1::-1], annot=False, cmap='RdBu_r',
    xticklabels=False, yticklabels=yticks, cbar=False, ax=ax)
ax.set_title('Title 1')
ax.set_aspect('equal')

ax = plt.subplot(2, 2, 2)
sns.heatmap(
    result1.iloc[-1::-1, -1::-1], annot=False, cmap='RdBu_r',
    xticklabels=False, yticklabels=False, cbar=False, ax=ax)
ax.set_title('Title 2')
ax.set_aspect('equal')

ax = plt.subplot(2, 2, 3)
sns.heatmap(
    result2.iloc[-1::-1, -1::-1], annot=False, cmap='RdBu_r',
    xticklabels=xticks, yticklabels=yticks, cbar=False, ax=ax)
ax.set_title('Title 3')
ax.set_aspect('equal')

ax = plt.subplot(2, 2, 4)
sns.heatmap(
    result3.iloc[-1::-1, -1::-1], annot=False, cmap='RdBu_r',
    xticklabels=xticks, yticklabels=False, cbar=True, cbar_ax=cbar_ax, ax=ax)
ax.set_title('Title 4')
ax.set_aspect('equal')
fig.tight_layout(rect=[0, 0, .9, 1])

References

One colorbar for seaborn heatmaps in subplot

How can I set the aspect ratio in matplotlib?

enter image description here

Upvotes: 3

Related Questions