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Add DataFrameGroupBy.corr

See original GitHub issue

Pandas allows for group-wise computation of the correlation coefficient.

In [4]: df = pd.DataFrame(np.random.randn(100, 4))

In [5]: df = pd.DataFrame(np.random.randn(100, 4), columns=list('abcd'))

In [6]: df['key'] = np.random.randint(0, 4, size=100)

In [7]: ddf = dd.from_pandas(df, 2)

In [8]: df.groupby('key').corr()
Out[8]:
              a         b         c         d
key
0   a  1.000000  0.012920  0.134284  0.087320
    b  0.012920  1.000000  0.169226 -0.318727
    c  0.134284  0.169226  1.000000  0.183607
    d  0.087320 -0.318727  0.183607  1.000000
1   a  1.000000 -0.010823 -0.351167 -0.156504
    b -0.010823  1.000000 -0.056893 -0.134058
    c -0.351167 -0.056893  1.000000 -0.188640
    d -0.156504 -0.134058 -0.188640  1.000000
2   a  1.000000  0.062685 -0.211482  0.239097
    b  0.062685  1.000000 -0.085522  0.219293
    c -0.211482 -0.085522  1.000000 -0.347176
    d  0.239097  0.219293 -0.347176  1.000000
3   a  1.000000 -0.078373  0.070477 -0.185380
    b -0.078373  1.000000  0.218543  0.053537
    c  0.070477  0.218543  1.000000  0.070091
    d -0.185380  0.053537  0.070091  1.000000

xref https://github.com/dask/dask/issues/4372

cc @quasiben, @jangorecki

Issue Analytics

State:
Created 4 years ago
Comments:9 (8 by maintainers)

Top GitHub Comments

2reactions

quasibencommented, Aug 15, 2019

I can finish up with corr – shouldn’t be too difficult. I dropped it from the original PR

1reaction

jakirkhamcommented, Aug 19, 2019

Please see Ben’s PR ( https://github.com/dask/dask/pull/5296 ).

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