Is it possible to widen the linewidth for sepcific columns and rows in a seaborn heatmap?
For example, can this heatmap
import numpy as np; np.random.seed(0)
import seaborn as sns; sns.set()
uniform_data = np.random.rand(10, 12)
ax = sns.heatmap(uniform_data, linewidths=1.0)
be transformed into something like this:
![enter image description here](https://i.stack.imgur.com/tLeJd.png)
It's possible, but may be a lot of work. A possible solution might look like shown below. It involves plotting 6 different heatmaps and adjusting the spacings such that it looks okish. One then also needs to synchronize the colorscaling and manually set the colorbar.
import matplotlib
import matplotlib.pyplot as plt
import numpy as np; np.random.seed(0)
import seaborn as sns; sns.set()data = np.random.rand(10, 12)asp = data.shape[0]/float(data.shape[1])
figw = 8
figh = figw*aspcmap = plt.cm.copper
norm = matplotlib.colors.Normalize(vmin= data.min(), vmax= data.max())gridspec_kw = {"height_ratios":[9,1], "width_ratios" : [4,5,3]}
heatmapkws = dict(square=False, cbar=False, cmap = cmap, linewidths=1.0, vmin= data.min(), vmax= data.max() )
tickskw = dict(xticklabels=False, yticklabels=False)left = 0.07; right=0.87
bottom = 0.1; top = 0.9
fig, axes = plt.subplots(ncols=3, nrows=2, figsize=(figw, figh), gridspec_kw=gridspec_kw)
plt.subplots_adjust(left=left, right=right,bottom=bottom, top=top, wspace=0.1, hspace=0.1*asp )
sns.heatmap(data[:9,0:4], ax=axes[0,0], xticklabels=False, yticklabels=True, **heatmapkws)
sns.heatmap(data[:9,4:9], ax=axes[0,1], xticklabels=False, yticklabels=False, **heatmapkws)
sns.heatmap(data[:9,9:12], ax=axes[0,2],xticklabels=False, yticklabels=False, **heatmapkws)sns.heatmap(data[9:,:4], ax=axes[1,0], xticklabels=True, yticklabels=True, **heatmapkws)
sns.heatmap(data[9:,4:9], ax=axes[1,1], xticklabels=True, yticklabels=False, **heatmapkws)
sns.heatmap(data[9:,9:12], ax=axes[1,2], xticklabels=True, yticklabels=False,**heatmapkws)axes[1,0].set_yticklabels([9])
axes[1,1].set_xticklabels([4,5,6,7,8])
axes[1,2].set_xticklabels([9,10,11])cax = fig.add_axes([0.9,0.1,0.03,0.8])
sm = matplotlib.cm.ScalarMappable(cmap=cmap, norm=norm)
sm.set_array([])
fig.colorbar(sm, cax=cax)plt.show()
![enter image description here](https://i.stack.imgur.com/Poe9X.png)