Hi,
I'm just getting used to the rpy module and so far I think it's pretty
great. One thing I haven't figured out though is how to print R
formatting. Here's my exact problem. I want to print the "summary" of an
lm object in the same format that it prints in R. Here's the R version:
> y = c(3,4,5,6)
> x = c(1,1,2,2)
> summary(lm(y~x))
Call:
lm(formula = y ~ x)
Residuals:
1 2 3 4
-0.5 0.5 -0.5 0.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.5000 1.1180 1.342 0.312
x 2.0000 0.7071 2.828 0.106
Residual standard error: 0.7071 on 2 degrees of freedom
Multiple R-Squared: 0.8, Adjusted R-squared: 0.7
F-statistic: 8 on 1 and 2 DF, p-value: 0.1056
>
The python version is
>>> data = {"y":[1,2,3,4],"x":[1,1,2,2]}
>>> lm = with_mode(0,r.lm)(r("y~x"),data)
>>> print r.summary(lm)
{'terms': <Robj object at 0xb7d3e2c0>, 'fstatistic': {'dendf': 2.0, 'value':
8.0000000000000036, 'numdf': 1.0}, 'aliased': {'x': False, '(Intercept)':
False}, 'df': [2, 2, 2], 'call': <Robj object at 0xb7d3e2a0>, 'residuals':
{'1': -0.49999999999999972, '3': -0.50000000000000011, '2':
0.49999999999999983, '4': 0.49999999999999994}, 'adj.r.squared':
0.70000000000000007, 'cov.unscaled': array([[ 2.5, -1.5],
[-1.5, 1. ]]), 'r.squared': 0.80000000000000004, 'sigma':
0.70710678118654735, 'coefficients': array([[-0.5 , 1.11803399, -
0.4472136 , 0.69848866],
[ 2. , 0.70710678, 2.82842712, 0.10557281]])}
>>>
Is there anyway to get the print statement to give me the same nice
formatting as I get in R? Thanks,
David
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