Run an OLS regression with Pandas Data Frame

Question

I have a pandas data frame and I would like to able to predict the values of column A from the values in columns B and C. Here is a toy example:

Answer 1

I don't know if this is new in sklearn or pandas, but I'm able to pass the data frame directly to sklearn without converting the data frame to a numpy array or any other data types.

from sklearn import linear_model

reg = linear_model.LinearRegression()
reg.fit(df[['B', 'C']], df['A'])

>>> reg.coef_
array([  4.01182386e-01,   3.51587361e-04])