mikkom - 1 year ago 288
Python Question

# Pandas: How to drop self correlation from correlation matrix

I'm trying to find highest correlations for different columns with pandas. I know can get correlation matrix with

``````df.corr()
``````

I know I can get the highest correlations after that with

``````df.sort()
df.stack()
df[-5:]
``````

The problem is that these correlation also contain values for column with the column itself (1). How do I remove these columns that contain correlation with self? I know I can remove them by removing all 1 values but I don't want to do that as there might be actual 1 correlations too.

Say you have

``````corrs = df.corr()
``````

Then the problem is with the diagonal elements, IIUC. You can easily set them to some negative value, say -2 (which will necessarily be lower than all correlations) with

``````np.fill_diagonal(corrs.values, -2)
``````

Example

(Many thanks to @Fabian Rost for the improvement & @jezrael for the DataFrame)

``````import numpy as np
df=pd.DataFrame( {
'one':[0.1, .32, .2, 0.4, 0.8],
'two':[.23, .18, .56, .61, .12],
'three':[.9, .3, .6, .5, .3],
'four':[.34, .75, .91, .19, .21],
'zive': [0.1, .32, .2, 0.4, 0.8],
'six':[.9, .3, .6, .5, .3],
'drive':[.9, .3, .6, .5, .3]})
corrs = df.corr()
np.fill_diagonal(corrs.values, -2)
>>> corrs
drive   four    one six three   two zive
drive   -2.000000   -0.039607   -0.747365   1.000000    1.000000    0.238102    -0.747365
four    -0.039607   -2.000000   -0.489177   -0.039607   -0.039607   0.159583    -0.489177
one -0.747365   -0.489177   -2.000000   -0.747365   -0.747365   -0.351531   1.000000
six 1.000000    -0.039607   -0.747365   -2.000000   1.000000    0.238102    -0.747365
three   1.000000    -0.039607   -0.747365   1.000000    -2.000000   0.238102    -0.747365
two 0.238102    0.159583    -0.351531   0.238102    0.238102    -2.000000   -0.351531
zive    -0.747365   -0.489177   1.000000    -0.747365   -0.747365   -0.351531   -2.000000
``````
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