CODEWITHSUNDEEP
pythonmatplotlibseaborn
Han Zhengzu
Han Zhengzu

Reputation: 3842

Change xticklabels fontsize of seaborn heatmap

Here is my question:
I plot 7 variable's coefficient using sns.clustermap()

My attempt

Add

My code:

 ds =  pd.read_csv("xxxx.csv")
 corr = ds.corr().mul(100).astype(int)
 
 cmap = sns.diverging_palette(h_neg=210, h_pos=350, s=90, l=30, as_cmap=True)

 sns.clustermap(data=corr_s, annot=True, fmt='d',cmap = "Blues",annot_kws={"size": 16},)

Upvotes: 45

Views: 138761

Answers (2)

5norre
5norre

Reputation: 813

Or just use the set_xticklabels:

g = sns.clustermap(data=corr_s, annot=True, fmt='d',cmap = "Blues")
g.ax_heatmap.set_xticklabels(g.ax_heatmap.get_xmajorticklabels(), fontsize = 16)

To get different colors for the ticklabels:

import matplotlib.cm as cm
colors = cm.rainbow(np.linspace(0, 1, corr_s.shape[0]))
for i, ticklabel in enumerate(g.ax_heatmap.xaxis.get_majorticklabels()):
    ticklabel.set_color(colors[i])

Upvotes: 37

Nelewout
Nelewout

Reputation: 6554

Consider calling sns.set(font_scale=1.4) before plotting your data. This will scale all fonts in your legend and on the axes.

My plot went from this, enter image description here

To this,

enter image description here

Of course, adjust the scaling to whatever you feel is a good setting.

Code:

sns.set(font_scale=1.4)
cmap = sns.diverging_palette(h_neg=210, h_pos=350, s=90, l=30, as_cmap=True)
sns.clustermap(data=corr, annot=True, fmt='d', cmap="Blues", annot_kws={"size": 16})

Upvotes: 88

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