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I am running OLS regression using pandas.stats.api.ols using a groupby with the following code:

from pandas.stats.api import ols
df=pd.read_csv(r'F:\file.csv')

result=df.groupby(['FID']).apply(lambda d: ols(y=d.loc[:, 'MEAN'], x=d.loc[:, ['Accum_Prcp', 'Accum_HDD']]))
for i in result:
    x=pd.DataFrame({'FID':i.index, 'delete':i.values})
    frame = pd.concat([x,DataFrame(x['delete'].tolist())], axis=1, join='outer')
    del frame['delete']
    print frame

but this returns the error:

AttributeError: 'OLS' object has no attribute 'index'

I have about 2,000 items in my group by and when I print each one out they look something like this:

-

------------------------Summary of Regression Analysis-------------------------

Formula: Y ~ <Accum_Prcp> + <Accum_HDD> + <intercept>

Number of Observations:         79
Number of Degrees of Freedom:   3

R-squared:         0.1242
Adj R-squared:     0.1012

Rmse:              0.1929

F-stat (2, 76):     5.3890, p-value:     0.0065

Degrees of Freedom: model 2, resid 76

-----------------------Summary of Estimated Coefficients------------------------
      Variable       Coef    Std Err     t-stat    p-value    CI 2.5%   CI 97.5%
--------------------------------------------------------------------------------
    Accum_Prcp     0.0009     0.0003       3.28     0.0016     0.0004     0.0015
     Accum_HDD     0.0000     0.0000       1.98     0.0516     0.0000     0.0000
     intercept     0.4750     0.0811       5.86     0.0000     0.3161     0.6340
---------------------------------End of Summary---------------------------------

I want to be able to export each one to a csv so that I can view them individually.

Stefan
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Stefano Potter
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2 Answers2

11

As of statsmodels 0.9, the Summary class supports export to multiple formats, including CSV and text:

import numpy as np
import statsmodels.api as sm
import statsmodels.formula.api as smf

dat = sm.datasets.get_rdataset("Guerry", "HistData").data
results = smf.ols('Lottery ~ Literacy + np.log(Pop1831)', data=dat).fit()

with open('summary.txt', 'w') as fh:
    fh.write(results.summary().as_text())

with open('summary.csv', 'w') as fh:
    fh.write(results.summary().as_csv())

The output of as_csv() is not machine-readable. Dumping results parameters with repr() would be.

Anton Tarasenko
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4

In order to write out the result of pandas.stats.api.ols, use a text file to match the output format, for instance:

from pandas.stats.api import ols
grps = df.groupby(['FID'])
for fid, grp in grps:
    result = ols(y=grp.loc[:, 'MEAN'], x=grp.loc[:, ['Accum_Prcp', 'Accum_HDD']])

    text_file = open("Output {}.txt".format(fid), "w")
    text_file.write(result.summary)
    text_file.close()
Stefan
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  • this returned, `File "F:/python codes/OLS_regress.py", line 35, in text_file.write(result) TypeError: expected a string or other character buffer object` – Stefano Potter Apr 01 '16 at 17:46
  • added `.summary()` to `result`, which should be an `OLS` object with that methods, which in turn produces the text output. See https://github.com/pydata/pandas/blob/master/pandas/stats/ols.py – Stefan Apr 01 '16 at 17:49
  • hmm, still returns `File "F:/python codes/OLS_regress.py", line 35, in text_file.write(result.summary()) TypeError: 'str' object is not callable`, Ill keep playing around with it though – Stefano Potter Apr 01 '16 at 17:52
  • It's a property, not method, so goes without the `()`, see update. – Stefan Apr 01 '16 at 17:55
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    For `statsmodels` `0.8.0`, there is `result.summary().as_text()`. – Stefan Oct 27 '16 at 20:37