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I create a corr() df out of an original df. The corr() df came out 70 X 70 and it is impossible to visualize the heatmap... sns.heatmap(df). If I try to display the corr = df.corr(), the table doesn't fit the screen and I can see all the correlations. Is it a way to either print the entire df regardless of its size or to control the size of the heatmap?

enter image description here

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  • $\begingroup$ I'm a little confused, do you want to print df.corr() or change the size of the heatmap? $\endgroup$ – Icyblade Mar 13 '17 at 1:52
  • $\begingroup$ @Gilbert You can do masking of the heatmap such that either the upper half or the lower half are only displayed $\endgroup$ – Nain Mar 13 '17 at 9:45
  • $\begingroup$ Ideally, I want to increase the heatmap size. $\endgroup$ – Gilbert Mar 13 '17 at 14:47
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I found out how to increase the size of my plot with the following code...

plt.subplots(figsize=(20,15))
sns.heatmap(corr)

enter image description here

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  • $\begingroup$ Check the answer yourself please :-) $\endgroup$ – Icyblade Mar 14 '17 at 7:15
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This would also work.

plt.figure(figsize=(20,15))
ax=subplot(111)
sns.heatmap(corr,ax=ax)
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plt.figure(figsize=(20,15))

plt is not always defined, I can use seaborn without plt.

To use the above line you need to also import plt like:

from matplotlib import plt
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  • $\begingroup$ import matplotlib.pyplot as plt $\endgroup$ – grofte Apr 8 '18 at 12:22
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The basic idea is to increase the default figure size in your plotting tool. You need to import matplotlib and set either default figure size or just the current figure size to a bigger one. Also, seaborn is built on top of matplotlib. You need to install and import matplitlib to make the best use of seaborn library.

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This will also work and allows for scale to be parameterized. Figure size can even be adjusted after plotting.

fig = plt.gcf()  # or by other means, like plt.subplots
figsize = fig.get_size_inches()
fig.set_size_inches(figsize * 1.5)  # scale current size by 1.5

fig.set_size_inches

fig.get_size_inches

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