Given this heat map:
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_da
iterating on the solution of @mwaskom, without creating the colorbar yourself:
import numpy as np
import seaborn as sns
data = np.random.rand(8, 12)
ax = sns.heatmap(data, vmin=0, vmax=1)
cbar = ax.collections[0].colorbar
cbar.set_ticks([0, .2, .75, 1])
cbar.set_ticklabels(['low', '20%', '75%', '100%'])