I have a DataFrame object stocks
filled with stock returns. I have another DataFrame object industries
filled with industry returns. I want to find each stock's correlation with each industry.
import numpy as np
np.random.seed(123)
df1=pd.DataFrame( {'s1':np.random.randn(10000), 's2':np.random.randn(10000) } )
df2=pd.DataFrame( {'i1':np.random.randn(10000), 'i2':np.random.randn(10000) } )
The expensive way to do this is to merge the two DataFrame objects, calculate correlation, and then throw out all the stock to stock and industry to industry correlations. Is there a more efficient way to do this?
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