How to extract a particular value from the OLS-summary in Pandas?

Question

is it possible to get other values (currently I know only a way to get beta and intercept) from the summary of linear regression in pandas? I need to get R-squared. Here is

Answer 1

try:

print model.r2

for example:

import pandas as pd
from pandas import Panel
from pandas.io.data import DataReader
import scikits.statsmodels.api as sm

symbols = ['MSFT', 'GOOG', 'AAPL']

data = dict((sym, DataReader(sym, "yahoo")) for sym in symbols)

panel = Panel(data).swapaxes('items', 'minor')

close_px = panel['Close']

# convert closing prices to returns
rets = close_px / close_px.shift(1) - 1
model = pd.ols(y=rets['AAPL'], x=rets.ix[:, ['GOOG']])
print model.r2

Docs: http://statsmodels.sourceforge.net/stable/index.html

Answer 2

Docs handling the results of the regression - this will allow you to extract a number of values from your regression results:

# Given
model = ols(y=rets['AAPL'], x=rets.ix[:, ['GOOG']])

In the case of r-squared use:

# retrieving model's r-squared value
model.rsquared

and in the case of p-values use:

# return p-values and corresponding coefficients in model
model.pvalues

For more parameters (fvalues ess) please refer to the doc