Matthew, we posted the release of 0.14.1 last night. Are these picked up
and build here automatically?
https://nipy.bic.berkeley.edu/scipy_installers/
thanks
Jeff
On Saturday, May 17, 2014 7:22:00 AM UTC-4, Jeff wrote:
>
> Hi,
>
> I'm pleased to announce the availability of
How does the build trigger? If its just a matter of clicking on something
when released. I think we can handle that :)
On Saturday, May 17, 2014 7:22:00 AM UTC-4, Jeff wrote:
>
> Hi,
>
> I'm pleased to announce the availability of the first release candidate of
> Pandas
!
Jeff
On Sunday, February 28, 2016 at 11:50:57 AM UTC-5, John E wrote:
>
> I hope this doesn't come across as a trivial, semantical question, but...
>
> The initial releases of the last 2 or so versions have been labelled as
> "release candidates" but still say
well the SAS reader works (i.e.
> how fast). I hate SAS myself, but this would be a really, really nice
> feature for my organization and likely increase adoption of python & pandas.
>
>
>
> On Sunday, February 28, 2016 at 12:03:45 PM UTC-5, Jeff wrote:
>>
>>
>
Good afternoon,
The list migration has completed successfully. [EMAIL PROTECTED] is
the new address for this list.
Thank you,
Jeff
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talling fink, add 'unstable/main' to the 'Trees:' line in
/sw/etc/fink.conf, and run 'fink selfupdate'. That way you will get the
latest versions of all the packages.
Also, if you want the python 2.5 versions, substitute 'py25' for 'py24'.
-Jeff
ws display back to my home mac, is a useful feature.
It all comes down to what you feel comfortable with. Choice is good.
-Jeff
--
Jeffrey S. Whitaker Phone : (303)497-6313
NOAA/OAR/CDC R/PSD1FAX : (303)497-6449
325 BroadwayBoulder, CO, USA 80305-3
nsion
from Pyrex.Distutils import build_ext
setup(name = "accumulator",
cmdclass = {'build_ext': build_ext},
keywords = ["python","map projections","GIS","mapping","maps"],
ext_modules = [Extension("ac
Eric Firing wrote:
> I have been using Jeff Whitaker's netcdf4 interface with good results.
>
> I could not find the web page for it on a NOAA site--I think NOAA is
> reorganizing--but a search turned it up here. Maybe Jeff can provide
> a better link.
>
> http://net
.
Jeff Strunk
IT Administrator
Enthought, Inc.
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)]]
Thank you,
Jeff Strunk
IT Administrator
Enthought, Inc.
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On Tuesday 20 March 2007 11:54 am, David M. Cooke wrote:
> On Mon, Mar 19, 2007 at 12:54:51PM -0500, Jeff Strunk wrote:
> > Good afternoon,
> >
> > By request, I have installed the TracReSTMacro on the numpy, scipy, and
> > scikits tracs. This plugin allows you to
Thank you for letting me know. I restarted the server at 5:30pm central.
-Jeff
On Sunday 25 March 2007 1:42 pm, Christopher Hanley wrote:
> Hi,
>
> It appears that the subversion server is down for numpy.
>
> Chris
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Is this still causing trouble? I restarted apache about 20 minutes after you
sent this.
Thanks,
Jeff
On Friday 11 May 2007 9:06 am, Christopher Hanley wrote:
> I had that problem this morning as well. It appears to be a problem on
> the server side.
>
> Chris
>
> George Nur
On Friday 11 May 2007 3:46 pm, George Nurser wrote:
> Jeff,
>
> Sorry to bother you again on this, but it's certainly still giving the
> same problem.
> svn: REPORT request failed on '/svn/numpy/!svn/vcc/default'
> svn: REPORT of '/svn/numpy/!svn/vcc/de
; (I run a couple of Mediawiki sites, so it shouldn't take me long to do
> simple edits in MoinMoin.)
>
> -rex
>
Someone needs to add your wiki account to the EditorsGroup. What is your wiki
username?
Thanks,
Jeff
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On Sunday 10 June 2007 11:10:37 am Jeff Strunk wrote:
> On Saturday 09 June 2007 3:01:02 pm rex wrote:
> > While compiling Numpy using MKL9.1 is fresh in my mind, I'd like to
> > update some things in the /Installing_SciPy/Linux page. I've registered
> > as a user, b
; i.e., have code that works on arrays of multiple types. Does it support it
> now?
>
> Best,
Coming soon in version 0.16:
https://sage.math.washington.edu:8091/hudson/job/cython-docs/doclinks/1/src/userguide/fusedtypes.html
-Jeff
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s the
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(1000,)
Out[17]: 1000
What's the difference between z4 as a netCDF4.Variable and as a
numpy.ndarray?
the netcdf variable object just refers to the data in the file - only
when you slice the object is the data read in and converted to a numpy
array.
-Jeff
Now, if I use scipy
1.close()
> file2.close()
>
> ---
>
> But this will not work as only one attribute named "att" in file2 will
> be created. How should I do this?
> Thanks.
>
Try this:
for att in file1.ncattrs():
setattr(file2,att) = getattr(file1,att)
-Jeff
--
Jeffrey S. W
grep
> -Po '^[^#]+' | sort | uniq -c | sort -rn
>
> 146 y-p
> 97 jreback
> 14 Joris Van den Bossche
> 8 Phillip Cloud
> 8 Andy Hayden
> 6 unutbu
> 4 Skipper Seabold
> 3 TomAugspurger
> 3 Jeff Tratner
>
I am pretty sure that you guys test pandas master
but 1.8.1 looks good to me
> On Feb 24, 2014, at 4:42 PM, Charles R Harris
> wrote:
>
>
>
>
>> On Mon, Feb 24, 2014 at 1:54 PM, RayS wrote:
>> Has anyone alerted C Gohlke?
>> http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy
>>
>> - Ray
>
Dave,
your example is not a problem with numpy per se, rather that the default
generation is in local timezone (same as what python datetime does).
If you localize to UTC you get the results that you expect.
In [49]: dates = pd.date_range('01-Apr-2014', '04-Apr-2014', freq='H')[:-1]
In [50]: pd.
FYI
Here are docs for panda of timezone handling
wesm worked thru the various issues w.r.t. conversion, localization, and
ambiguous zone crossing.
http://pandas.pydata.org/pandas-docs/stable/timeseries.html#time-zone-handling
implementation is largely in here:
(underlying impl is a datetime64
https://github.com/pydata/pandas/releases>
A big thank you to everyone who contributed to this release!
Jeff
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Waeber
- David Jung
- David Stephens
- Douglas McNeil
- DSM
- Garrett Drapala
- Gouthaman Balaraman
- Guillaume Poulin
- hshimizu77
- hugo
- immerrr
- ischwabacher
- Jacob Howard
- Jacob Schaer
- jaimefrio
- Jason Sexauer
- Jeff Reback
- Jeffrey
the upgrade flag on pip is apparently recursive on all deps
On May 30, 2014, at 6:16 PM, Neal Becker wrote:
>
> pip install --user --up pandas
> Downloading/unpacking pandas from
> https://pypi.python.org/packages/source/p/pandas/pandas-0.14.0.tar.gz#md5=b775987c0ceebcc8d5ace4a1241c967a
> ...
sure would take a pr for that
anything 2 make setup easier!
> On May 31, 2014, at 1:50 AM, Ralf Gommers wrote:
>
>
>
>
>> On Sat, May 31, 2014 at 12:30 AM, Jeff Reback wrote:
>> the upgrade flag on pip is apparently recursive on all deps
>
> Indeed. This
The one pandas test failure that is valid: ERROR:
test_interp_regression (pandas.tests.test_generic.TestSeries)
has been fixed in pandas master / 0.14.1 (prob releasing in 1 month).
(the other test failures are for clipboard / network issues)
On Mon, Jun 9, 2014 at 7:21 PM, Christoph Gohlke
In pandas 0.14.0, generic whitespace IS parsed via the c-parser, e.g.
specifying '\s+' as a separator. Not sure when you were playing last with
pandas, but the c-parser has been in place since late 2012. (version 0.8.0)
http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#text-parsing-a
ok from pandas
we test with numpy master on Travis (which does pick up things!)
thanks
> On Jul 4, 2014, at 7:07 PM, Charles R Harris
> wrote:
>
>
>
>
>> On Fri, Jul 4, 2014 at 3:33 PM, Nathaniel Smith wrote:
>> On Fri, Jul 4, 2014 at 10:31 PM, Charles R Harris
>> wrote:
>> >
>> > On Fri,
pandas 0.14.1 scheduled for end of next week (was waiting to see schedule for
numpy 1.9) but works either way
> On Jul 4, 2014, at 7:41 PM, Nathaniel Smith wrote:
>
> On 5 Jul 2014 00:07, "Charles R Harris" wrote:
> >
> >
> >
> >
> > On Fri, Jul 4, 2014 at 3:33 PM, Nathaniel Smith wrote:
> >>
Hello,
We are proud to announce v0.14.1 of pandas, a minor release from 0.14.0.
This release includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug
fixes.
This was 1.5 months of work with 244 commits by 45 authors
Ray
Matthew builds Mac osx wheels for scipy stack (those are windows binaries)
thanks anyhow
> On Jul 11, 2014, at 12:10 PM, RayS wrote:
>
> At 04:56 AM 7/11/2014, you wrote:
>> Matthew, we posted the release of 0.14.1 last night. Are these
>> picked up and build here automatically?
>> http
in 0.15.0 pandas will have full fledged support for categoricals which in
effect allow u 2 map a smaller number of strings to integers
this is now in pandas master
http://pandas-docs.github.io/pandas-docs-travis/categorical.html
feedback welcome!
> On Jul 14, 2014, at 1:00 PM, Olivier Grisel
related recent issue: https://github.com/numpy/numpy/issues/4638
and pandas is now explicitly specifying the accumulator to avoid this
problem: https://github.com/pydata/pandas/pull/6954/files
pandas also implemented the Welfords method for rolling_var in 0.14.0, see
here: https://github.com/pydat
FYI pandas DOES use a very performant hash table impl for unique (and
value_counts). Sorted state IS maintained
by underlying Index implmentation.
https://github.com/pydata/pandas/blob/master/pandas/hashtable.pyx
In [8]: a = np.random.randint(10, size=(1,))
In [9]: %timeit np.unique(a)
1000 l
sily decide, hey
this is the most correct behavior, let's do it this way, nothing to break,
no back compat needed.
Jeff
On Sun, Sep 21, 2014 at 11:31 PM, Nathaniel Smith wrote:
> On Sun, Sep 21, 2014 at 7:50 PM, Stephan Hoyer wrote:
> > pandas has some hacks to support custom typ
memory usage (this only applies to using df.info())
There is really no performance impact here.
Pls let us know!
thanks
Jeff
>>> df.info(memory_usage=True)Int64Index:
>>> 1000 entries, 0 to 999Data columns (total 5 columns):date
>>> datetime6
v0.15.0rc1 Release <https://github.com/pydata/pandas/releases>
A big thank you to everyone who contributed to this release!
Jeff
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Hello,
We are proud to announce v0.15.0 of pandas, a major release from 0.14.1.
This release includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug
fixes.
This was 4 months of work with 420 commits by 79 authors e
you should have a read here/
http://wesmckinney.com/blog/?p=543
going below the 2x memory usage on read in is non trivial and costly in terms
of performance
> On Oct 26, 2014, at 4:46 AM, Saullo Castro wrote:
>
> I would like to start working on a memory efficient alternative for
> np.loadtx
usage (though ultimately still 2x); but
combined with memory mapping can provide a fixed resource utilization
> On Oct 26, 2014, at 9:41 AM, Daπid wrote:
>
>
>> On 26 October 2014 12:54, Jeff Reback wrote:
>> you should have a read here/
>> http://wesmckinney.com/blo
- Charalampos Papaloizou
- Chris Warth
- David Stephens
- Fabio Zanini
- Francesc Via
- Henry Kleynhans
- Jake VanderPlas
- Jan Schulz
- Jeff Reback
- Jeff Tratner
- Joris Van den Bossche
- Kevin Sheppard
- Matt Suggit
- Matthew Brett
- Phillip Cloud
s>
A big thank you to everyone who contributed to this release!
Jeff
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Hello,
We are proud to announce v0.16.0 of pandas, a major release from 0.15.2.
This release includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug
fixes.
This was 4 months of work by 60 authors encompassing 204 i
-
- Alfonso MHC
- Andy Hayden
- Artemy Kolchinsky
- Chris Gilmer
- Chris Grinolds
- Dan Birken
- David BROCHART
- David Hirschfeld
- David Stephens
- Dr. Leo
- Evan Wright
- Frans van Dunné
- Hatem Nassrat
- Henning Sperr
- Hugo Herter
- Jan Schulz
-
sky
- Bernard Willers
- Christer van der Meeren
- Christian Hudon
- Constantine Glen Evans
- Daniel Julius Lasiman
- Evan Wright
- Francesco Brundu
- Gaëtan de Menten
- Jake VanderPlas
- James Hiebert
- Jeff Reback
- Joris Van den Bossche
- Justin Lecher
- Ka Wo
you guys have an agenda?
I can be reached on my cell 917-971-6387
> On Jun 30, 2015, at 12:58 AM, Nathaniel Smith wrote:
>
>> On Fri, Jun 26, 2015 at 2:32 AM, Nathaniel Smith wrote:
>> Hi all,
>>
>> In a week and a half, this is happening:
>>
>>https://github.com/numpy/numpy/wiki/SciPy-2
FYI pandas followed the same pattern to deprecate float indexers (except for
indexing in a Float64Index) about a year ago
see here:
http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0140-deprecations
> On Jul 2, 2015, at 9:18 PM,
> wrote:
>
>
>
>> On Thu, Jul 2, 2015 at 8
Pandas has for quite a while has a travis build where we install numpy
master and then run our test suite.
e.g. here: https://travis-ci.org/pydata/pandas/jobs/77256007
Over the last year this has uncovered a couple of changes which affected
pandas (mainly using something deprecated which was turn
2.7
and Python 3.4 are all available.
conda install pandas -c pandas
Thanks to all who made this release happen. It is a very large release!
Jeff
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osx/linux) are all available.
conda install pandas -c pandas
Thanks to all who made this release happen. It is a very large release!
Jeff
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;
>> On Sunday, October 4, 2015 at 7:36:26 AM UTC+2, Matthew Brett wrote:
>> Hi,
>>
>> On Sat, Oct 3, 2015 at 2:33 PM, Jeff Reback wrote:
>> > Hi,
>> >
>> > I'm pleased to announce the availability of the second release candidate
onda is:
- conda install pandas
windows wheels are courtesy of Christoph Gohlke and are built on Numpy 1.9
macosx wheels are courtesy of Matthew Brett
*Issues:*
Please report any issues on our issue tracker
<https://github.com/pydata/pandas/issues>:
Thanks to all who made this
Here another oddity to add to the list
In [28]: issubclass(np.datetime64,np.integer)
Out[28]: False
In [29]: issubclass(np.timedelta64,np.integer)
Out[29]: True
On Tue, Oct 13, 2015 at 5:44 PM, Chris Barker wrote:
> On Sun, Oct 11, 2015 at 8:38 PM, Stephan Hoyer wrote:
>
>> Currently, NaT (n
gt; Also -- if we do want a fast read numbers from text files function (which
>>>> would be nice, actually), it really should get a new name anyway.
>>>>
>>>> (and the hopefully coming new dtype system would make it easier to write
>
> On Oct 23, 2015, at 6:49 PM, Nathaniel Smith wrote:
>
> On Oct 23, 2015 3:30 PM, "Jeff Reback" wrote:
> >
> > On Oct 23, 2015, at 6:13 PM, Charles R Harris
> > wrote:
> >
> >>
> >>
> >> On Thu, Oct 22, 2015 at 5:47 PM
on our issue tracker
<https://github.com/pydata/pandas/issues>:
Jeff
*Thanks to all of the contributors*
* - Aleksandr Drozd - Alex Chase - Anthonios Partheniou - BrenBarn - Brian
J. McGuirk - Chris - Christian Berendt - Christ
pandas is going to drop
2.6 and 3.3 next release at end of Jan
(3.2 dropped in 0.17, in October)
I can be reached on my cell 917-971-6387
> On Dec 3, 2015, at 6:00 PM, Bryan Van de Ven wrote:
>
>
>> On Dec 3, 2015, at 4:59 PM, Eric Firing wrote:
>>
>> Chuck,
>>
>> I would support droppin
just my 2c
it's fairly straightforward to add a test to the Travis matrix to grab numpy
wheels built numpy wheels (works for conda or pip installs).
so in pandas we r testing 2.7/3.5 against numpy master continuously
https://github.com/pydata/pandas/blob/master/ci/install-3.5_NUMPY_DEV.sh
> O
FYI also useful to simply close by time - say older than 6 months with a
message for the writer to reopen if they want to work on it
then u don't get too many stale ones
my 2c
> On Jan 31, 2016, at 2:10 PM, Charles R Harris
> wrote:
>
> Hi All,
>
> There are now 130 open numpy pull request
In [10]: pd.options.display.max_rows=10
In [13]: np.random.seed(1234)
In [14]: c = np.random.randint(0,32,size=10)
In [15]: v = np.arange(10)
In [16]: df = DataFrame({'v' : v, 'c' : c})
In [17]: df
Out[17]:
c v
0 15 0
1 19 1
2 6 2
3 21
3
9998 7
10
[1 rows x 1 columns]
On Sat, Feb 13, 2016 at 1:39 PM, Jeff Reback wrote:
> In [10]: pd.options.display.max_rows=10
>
> In [13]: np.random.seed(1234)
>
> In [14]: c = np.random.randint(0,32,size=10)
>
> In [15]: v = np.arange(10)
>
> In [1
o/pandas-docs-travis/install.html#installing-pandas-with-anaconda>
from
our development channel. Builds for osx-64,linux-64,win-64 for Python 2.7
and Python 3.5 are all available.
conda install pandas=v0.18.0rc1 -c pandas
Thanks to all who made this release happen. It is a very large release!
J
s, see
here
<https://github.com/pydata/pandas/blob/master/pandas/indexes/range.py#L274>
though didn't officially benchmark thes.
Jeff
On Mon, Feb 15, 2016 at 11:13 AM, Antony Lee
wrote:
> Indeed:
>
> In [1]: class C:
> def __getitem__(self, i):
> if i <
https://github.com/pydata/pandas/releases/tag/v0.18.0rc1
On Mon, Feb 15, 2016 at 12:51 PM, Derek Homeier <
de...@astro.physik.uni-goettingen.de> wrote:
> On 14 Feb 2016, at 1:53 am, Jeff Reback wrote:
> >
> > I'm pleased to announce the availability of the first rel
#installing-pandas-with-anaconda>
from
our development channel. Builds for osx-64,linux-64,win-64 for Python 2.7
and Python 3.5 are all available.
conda install pandas=v0.18.0rc2 -c pandas
Thanks to all who made this release happen. It is a very large release!
Jeff
___
ailable on PyPI
<https://pypi.python.org/pypi/pandas>
Installation via conda is:
- conda install pandas
windows wheels are courtesy of Christoph Gohlke and are built on Numpy 1.10
macosx wheels are courtesy of Matthew Brett.
*Issues:*
Please report any issues on our issue tracker
<htt
t on Numpy 1.10. Macosx wheels are courtesy of Matthew
Brett.
Installation via conda is: conda install pandas
currently its available via the conda-forge channel: conda install pandas
-c conda-forge
It will be available on the main channel shortly.
Please report any issues on our issue tracker
<https://
This is trivial in pandas. a simple groupby.
In [6]: data = [[ 'a', 27, 14.5 ],['b', 12, 99.0],['a', 17, 100.3], ['b',
12, -329.0]]
In [7]: df = DataFrame(data, columns=list('ABC'))
In [8]: df
Out[8]:
A B C
0 a 27 14.5
1 b 12 99.0
2 a 17 100.3
3 b 12 -329.0
In [9]: df.gro
I tried to install scipy, but I get the error with not being able to find
get_info() from numpy.distutils.misc_util. I read that you need the SVN
version of numpy to fix this. I recompiled numpy and reinstalled from the
SVN, which says is version 1.3.0 (was using 1.4.1 version before) and that
fu
8, 2010 at 10:41 AM, Pauli Virtanen wrote:
> Tue, 08 Jun 2010 09:47:41 -0400, Jeff Hsu wrote:
> > I tried to install scipy, but I get the error with not being able to
> > find get_info() from numpy.distutils.misc_util. I read that you need
> > the SVN version of numpy to fix t
Check which version of numpy python is importing with "import numpy; print
numpy.__file__". I had a similar question and this worked after I removed
that installation of numpy. I think the enthought distro installs it
somewhere else that has priority.
On Tue, Jun 8, 2010 at 10:30 PM, Nick Matzk
d returns
numpy object arrays, where the elements of the object arrays are
themselves 1d numpy arrays. I don't think there is any other way to do
it. In your example, the 'ragged' array would be a 1d numpy array with
dtype='O', and the individual elements would be 1
e conversation, does HDF and/or pytables
> have a standard way of dealing with this?
>
> On 3/7/11 9:37 AM, Jeff Whitaker wrote:
>> Chris: The netcdf4-python modules reads netcdf vlen arrays
> arethose a netcdf4 feature?
Chris:
Yes, although I don't think many people are
in seed
> super(Random, self).seed(a)
> SystemError: error return without exception set
>
> Any ideas?
> I've had numpy/scipy installed in the past, but recently had to wipe
> everything and start from scratch. Everything shoul
in seed
> super(Random, self).seed(a)
> SystemError: error return without exception set
>
> Any ideas?
> I've had numpy/scipy installed in the past, but recently had to wipe
> everything and start from scratch. Everything should be pr
here's only one that I know of - http://code.google.com/p/netcdf4-python.
-Jeff
--
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Meteorologist FAX: (303)497-6449
NOAA/OAR/PSD R/PSD1Email : jeffrey.s.whita...@noaa.gov
325 BroadwayOffice :
Same problem with 1.3.0rc1
Jeff Blaine wrote:
> Aside from this, the website for NumPy should have a link to the
> list subscription address, not a link to the list itself (which
> cannot be posted to unless one is a member).
>
> Python 2.4.2 (#2, Dec 6 2006, 17:18:19)
> [GC
> What version of glibc do you have?
None. Solaris does not use GNU libc.
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FWIW, I solved this just now by removing Sun Studio from
my PATH before build. It's clear that's a workaround
though and the build process failed to determine something
properly.
Jeff Blaine wrote:
>> What version of glibc do you have?
>
> None. Solaris
ay to tell if the individual fields are masked than
accessing ._fieldmask?
Thanks,
Jeff Garrett
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