Change tick size on colorbar of seaborn heatmap
Question:
I want to increase the tick label size corresponding to the colorbar in a heatmap plot created using the seaborn module. As an example:
import seaborn as sns
import pandas as pd
import numpy as np
arr = np.random.random((3,3))
df = pd.DataFrame(arr)
ax = sns.heatmap(arr)
Usually I would change the labelsize keyword using the tick_params method on a colorbar axes object, but with the heatmap() function I can only pass kwargs to the colorbar constructor. How can I modify the tick label size for the colorbar in this plot?
Answers:
Once you call heatmap the colorbar axes will get a reference at the axes attribute of the figure object. So you could either set up the figure ahead of time or get a reference to it after plotting with ax.figure and then pull the colorbar axes object out that way:
import seaborn as sns
import pandas as pd
import numpy as np
arr = np.random.random((3,3))
df = pd.DataFrame(arr)
ax = sns.heatmap(arr)
cax = ax.figure.axes[-1]
cax.tick_params(labelsize=20)
A slightly different way that avoids gcf():
import seaborn as sns
import pandas as pd
import numpy as np
arr = np.random.random((3,3))
df = pd.DataFrame(arr)
fig, ax = plt.subplots()
sns.heatmap(arr, ax=ax)
ax.tick_params(labelsize=20)
I almost always start my plots this way, by explicitly creating a fig and ax object. It’s a bit more verbose, but since I tend to forget my matplotlib-foo, I don’t get confused with what I’m doing.
I want to increase the tick label size corresponding to the colorbar in a heatmap plot created using the seaborn module. As an example:
import seaborn as sns
import pandas as pd
import numpy as np
arr = np.random.random((3,3))
df = pd.DataFrame(arr)
ax = sns.heatmap(arr)
Usually I would change the labelsize keyword using the tick_params method on a colorbar axes object, but with the heatmap() function I can only pass kwargs to the colorbar constructor. How can I modify the tick label size for the colorbar in this plot?
Once you call heatmap the colorbar axes will get a reference at the axes attribute of the figure object. So you could either set up the figure ahead of time or get a reference to it after plotting with ax.figure and then pull the colorbar axes object out that way:
import seaborn as sns
import pandas as pd
import numpy as np
arr = np.random.random((3,3))
df = pd.DataFrame(arr)
ax = sns.heatmap(arr)
cax = ax.figure.axes[-1]
cax.tick_params(labelsize=20)
A slightly different way that avoids gcf():
import seaborn as sns
import pandas as pd
import numpy as np
arr = np.random.random((3,3))
df = pd.DataFrame(arr)
fig, ax = plt.subplots()
sns.heatmap(arr, ax=ax)
ax.tick_params(labelsize=20)
I almost always start my plots this way, by explicitly creating a fig and ax object. It’s a bit more verbose, but since I tend to forget my matplotlib-foo, I don’t get confused with what I’m doing.