> The original data was in CSV format. I read it in using pd.read_csv(). It > does have column names, but no row names. I don’t think numpy reads csv files I routinely read csv files using numpy.loadtxt https://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html
> And also, when I do a[2:5]-b[:3], it does not throw any “index out of range” > error. I was able to catch that, but in both Matlab and R. You get an error. > This is frustrating!! That's basic slicing behaviour of python. You might like it or not, but it's baked into the language: >>> [1,2][:10], [1,2][5:7] ([1, 2], []) One would need very good reasons to break this in case of a third-party library. András > ________________________________ > From: NumPy-Discussion > <numpy-discussion-bounces+tmrsg11=gmail....@python.org> on behalf of Juan > Nunez-Iglesias <jni.s...@gmail.com> > Sent: Friday, February 15, 2019 4:15 AM > To: Discussion of Numerical Python > Subject: Re: [Numpy-discussion] [SciPy-User] Why slicing Pandas column and > then subtract gives NaN? > > > I don’t have index when I read in the data. I just want to slice two series > to the same length, and subtract. That’s it! > > I also don’t what numpy methods wrapped within methods. They work, but hard > do understand. > > How would you do it? In Matlab or R, it’s very simple, one line. > > > Why are you using pandas at all? If you want the Matlab equivalent, use NumPy > from the beginning (or as soon as possible). I personally agree with you that > pandas is too verbose, which is why I mostly use NumPy for this kind of > arithmetic, and reserve pandas for advanced data table type functionality > (like groupbys and joining on indices). > > As you saw yourself, a.values[1:4] - b.values[0:3] works great. If you read > in your data into NumPy from the beginning, it’ll be a[1:4] - b[0:3] just > like in Matlab. (Or even better: a[1:] - b[:-1]). > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
