On 2011-10-05 02:48, William T. Martin wrote:
> I have a string s="70 75 none 80" that I would like to convert to an
> robjects.FloatVector f, which in R would be f<-(70, 75, NA, 80)
>
> Under py2-2.0, this works for me:
>
>>>> import rpy2.robjects as robjects
>>>> readings="70 80 none 90"
>>>> f=robjects.FloatVector(readings.split(" "))
>>>> print(f)
> [1] 70 80 NA 90
>
> Under py2 2.3.0dev, I get the following:
>
>>>> import rpy2.robjects as robjects
>>>> readings="70 80 none 90"
>>>> f=robjects.FloatVector(readings.split(" "))
> Traceback (most recent call last):
> File "<stdin>", line 1, in<module>
> File
> "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/vectors.py", line
> 402, in __init__
> obj = FloatSexpVector(obj)
> ValueError: Error while trying to convert element 2 to a double.
>
> What is the current way to get f<-(70, 75, NA, 80)?
You seem to be relying on R's "magic".
With Python:
>>> float("70")
70.0
>>> float("none")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: could not convert string to float: none
>>> float("None")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: could not convert string to float: None
If you want to do things on the Python side, you'll have to indicate how
to represent strings that are not numbers (Python's "better explicit
than implicit" ).
FloatVector([ro.NA_Real if x == "none" else float(x) for x in readings.split("
")])
> Thank you
>
> Bill
>
>
>
>
>
>
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definitive record of customers, application performance, security
threats, fraudulent activity and more. Splunk takes this data and makes
sense of it. Business sense. IT sense. Common sense.
http://p.sf.net/sfu/splunk-d2dcopy1
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