Apply datetime methods to timestamps results in numpy errors #2689

NigelCleland opened this Issue Jan 14, 2013 · 2 comments


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This may or may not be a bug. I'm unsure of which functionality you were intending.

I have a timestamp created by

rng = pd.date_range(start_date, periods = 100, freq='2H')
A = DataFrame(rng) # We'll leave it as a generic index for now, not important.

I then have a function which is applied to that dataframe via A.apply(f)

def f(x):
    return (x.hour,, x.month)

if I apply this functionality to the raw dataframe via .apply, this will result in a numpy.datetime64 error.

However, if I apply it to individual points.

E.g. f(A.ix[10]), then the correct functionality results.

I have determined that this is due to a difference between the types of the two

e.g. A.dtype = dtype('datetime64[n]s')

type(A.ix[10]) = pandas.tslib.Timestamp

Thus to get around the issue above you may simply add the following functionality to the function

def f(x):
x = pd.Timestamp(x)
return (x.hour, x.month, x.year)

I am filing this as I'm unsure of what you're intended functionality is with this matter

wesm was assigned Jan 19, 2013


wesm commented Jan 20, 2013

Taking a look at this. A guideline for future posting issues: make sure the code you post works (there were multiple typos, I fixed a couple of them) and the exact code that generated the error is listed


wesm commented Jan 20, 2013

fixed along with #2627

wesm closed this Jan 20, 2013

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