Mailman 3 March 2017 - Pandas-dev

Fwd: Doodle: Link for poll "Pandas Dev Meeting"
by Jeff Reback April 6, 2017

April 6, 2017

If you have not already responded and want to participate, please do so. Jeff ---------- Forwarded message ---------- From: Doodle <mailer(a)doodle.com> Date: Mon, Mar 27, 2017 at 3:21 PM Subject: Doodle: Link for poll "Pandas Dev Meeting" To: Jeff Reback <jeffreback(a)gmail.com> Hi Jeff Reback, You have initiated a poll "Pandas Dev Meeting" at Doodle. The link to your poll is: http://doodle.com/poll/acfmznfqzrhw5mhp Share this link with all those who should cast their votes. Do not forget to cast your vote, too. (If you did not initiate this poll, somebody must accidentally have used your e-mail address; simply ignore this e-mail, please.) - Your Doodle Team ---- Doodle AG, Werdstrasse 21, 8021 Zürich

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developer meeting
by Jeff Reback March 27, 2017

March 27, 2017

I sent a generic link, but here it is again: http://doodle.com/poll/ acfmznfqzrhw5mhp Ideally have a 1 hr meeting to discuss upcoming 0.20.0 release. I fixed the poll at 2pm EST, but if not convenient lmk and we can add another option. Jeff

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Pandas Dev Meeting
by Jeff Reback (via Doodle) March 27, 2017

March 27, 2017

Hi there, Jeff Reback (jeffreback(a)gmail.com) invites you to participate in the Doodle poll "Pandas Dev Meeting." Bi-Monthly developer meeting As we are coming upon the 0.20.0 release. Want to have some discussion about what to include (or not include). Participate now https://doodle.com/poll/acfmznfqzrhw5mhp?tmail=poll_invitecontact_participa… What is Doodle? Doodle is a web service that helps Jeff Reback to find a suitable date for meeting with a group of people. Learn more about how Doodle works. (https://doodle.com/features?tlink=checkOutLink&tmail=poll_invitecontact_par…) ---------------------------------------------------------------------- You have received this e-mail because "Jeff Reback" has invited you to participate in the Doodle poll "Pandas Dev Meeting." ---- Doodle is also available for iOS and Android. ---- Doodle AG, Werdstrasse 21, 8021 Zürich

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pandas daily wheels for linux / osx
by Jeff Reback March 21, 2017

March 21, 2017

We have recently enabled Travis to build daily wheels for linux & osx (currently 2.7, 3.5, 3.6 on linux, and 3.6 on osx). These are a snapshot of master at that time & tagged with the dev commits. These are pushed to the same location as numpy/scipy/matplotlib daily wheels. you can install like this. # install pandas wheel from master PRE_WHEELS=" https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackc… " pip install --pre --upgrade --timeout=60 -f $PRE_WHEELS pandas Big thank you to Matthew Brett for help setting this up! enjoy! Jeff

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appveyor
by Jeff Reback March 9, 2017

March 9, 2017

I enabled a pandas-dev appveyor account. next time you login you should be able to login using your github username (you have to pick from the drop-down). Hopefully the transition will work (may not on existing PR's) though. But it looks like its working on master. Jeff

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Should the sum of Series of all NaN return 0 or NaN ?
by Joris Van den Bossche March 2, 2017

March 2, 2017

For those not aware but potentially interested, want to point out that there is a (renewed) discussion going on about the question in the title, see https://github.com/pandas-dev/pandas/issues/9422. As a summary of what this is about: The question is what the sum of a Series of all NaNs should return (which is equivalent to an empty Series after skipping the NaNs): NaN or 0? In [1]: s = Series([np.nan]) In [2]: s.sum(skipna=True) # skipping NaNs is the default Out[2]: nan or 0 <---- DISCUSSION POINT In [3]: s.sum(skipna=False) Out[3]: nan The reason this is a discussion point has the following cause: the internal nansum implementation of pandas returns NaN. But, when bottleneck is installed, pandas will use bottlenecks implementation of nansum, which returns 0 (for the versions >= 1.0). Bottleneck changed the behaviour from returning NaN to returning 0 to model it after numpy's nansum function. This has the very annoying consequence that depending on whether bottleneck is installed or not (which is only an optional dependency), you get a different behaviour. This inconsistency is bad, and should be solved, and so we have to choose between both behaviours. I am not going to list pro's and con's here, for that you can read the comments in the github issues :-) (you can start here with the comments of today: https://github.com/pandas-dev/pandas/issues/9422#issuecomment-283502828) Regards, Joris

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