BUG: rolling.quantile does not return an interpolated result #16247

guillemborrell · 2017-05-05T06:52:13Z

Now computing the quantile of a rolling window matches the default of the rolling method in Series, DataFrame and np.percentile.

Fixes bugs #9413 and #16211

closes BUG: pandas rolling_quantile does not use interpolation #9413
tests added / passed
passes git diff upstream/master --name-only -- '*.py' | flake8 --diff
whatsnew entry

codecov · 2017-05-05T07:23:57Z

Codecov Report

Merging #16247 into master will decrease coverage by 0.01%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master   #16247      +/-   ##
==========================================
- Coverage   90.33%   90.32%   -0.02%     
==========================================
  Files         164      164              
  Lines       50890    50890              
==========================================
- Hits        45972    45966       -6     
- Misses       4918     4924       +6

Flag	Coverage Δ
#multiple	`88.1% <ø> (ø)`	⬆️
#single	`40.3% <ø> (-0.1%)`	⬇️

Impacted Files	Coverage Δ
pandas/io/gbq.py	`25% <0%> (-58.34%)`	⬇️
pandas/util/testing.py	`78.68% <0%> (-0.2%)`	⬇️
pandas/core/frame.py	`97.58% <0%> (-0.1%)`	⬇️
pandas/_version.py	`44.65% <0%> (+1.9%)`	⬆️

Continue to review full report at Codecov.

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codecov · 2017-05-05T07:24:05Z

Codecov Report

Merging #16247 into master will decrease coverage by 0.01%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master   #16247      +/-   ##
==========================================
- Coverage   90.98%   90.97%   -0.02%     
==========================================
  Files         161      161              
  Lines       49300    49304       +4     
==========================================
- Hits        44857    44852       -5     
- Misses       4443     4452       +9

Flag	Coverage Δ
#multiple	`88.74% <100%> (ø)`	⬆️
#single	`40.17% <0%> (-0.07%)`	⬇️

Impacted Files	Coverage Δ
pandas/core/window.py	`96.51% <100%> (+0.01%)`	⬆️
pandas/io/gbq.py	`25% <0%> (-58.34%)`	⬇️
pandas/core/frame.py	`97.71% <0%> (-0.1%)`	⬇️

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jaimefrio

PTAL, I think there are some corner cases that need taking care off, and have also a couple of enhancement suggestions.

Aside from those it LGTM.

jaimefrio · 2017-05-05T09:29:14Z

pandas/_libs/window.pyx

+                qhigh = (<double> (idx + 1)) / (<double>(nobs - 1))
+                vlow = skiplist.get(idx)
+                vhigh = skiplist.get(idx + 1)
+                output[i] = vlow + (vhigh - vlow) * \


The computation time is probably dominated by the skip list, but it still feels wrong to have three divisions in the innermost loop. And I think we can actually get rid of all of them! If this is correct:

qlow = i / (nobs - 1) qhigh = (i + 1) / (nobs - 1) (quantile - qlow) / (qhigh - qlow) = (q - i / (nobs - 1)) / ((i + 1 - i) / (nobs - 1)) = (nobs - 1) * q - i

It should be possible to simply write

output[i] = vlow + (vhigh - vlow) * (quantile * (nobs - 1) - idx)

It should be faster, although probably not much, but on top of that I think that the fact that quantile * (nobs - 1) - idx is the fractional part of quantile * (nobs - 1) makes the code a little more self explanatory?

Now implemented as suggested.

jaimefrio · 2017-05-05T09:33:34Z

pandas/_libs/window.pyx

-            output[i] = skiplist.get(idx)
+
+            # Exactly last point
+            if idx == nobs - 1:


This can only happen if quantile == 1.0, right? It might be worth removing the branch from the inner loop: I think we could actually redirect quantile == 1.0 to roll_max and quantile == 0.0 to roll_min? If I am not missing anything, these are asymptotically faster, O(n) vs O(n log w).

quantile == 1.0 and == 0.0 now fallback to roll_max and roll_min respectively

jaimefrio · 2017-05-05T09:46:38Z

pandas/_libs/window.pyx

+
+            # Interpolated quantile
+            else:
+                qlow = (<double> idx) / (<double>(nobs - 1))


Bad things (TM) happen if nobs == 1, not only because of the obvious division by zero here, but vhigh will index the skiplist out of bounds. Unless minp can be guaranteed to be at >= 2 upstream (I don't think it can!) we are going to have to guard against that possibility in the inner loop.

We could simply branch on nobs >= 1, which is probably more predictable and faster in the more common cases, or another possibility is to only compute vhigh and interpolate if quantile * (nobs - 1) != idx.

However this is fixed, a test with enough NaNs to have a single observation in some window, and min_periods=1, should certainly be added.

The branch that handled quantile == 1.0 also handled nobs == 1, that now is handled separately in the innermost loop. There may be more optimal ways to handle this case in a more external loop, but IMHO this change is not that bad, since this condition only happens when there's a single loop.

I have not added more tests, since TestMoments::test_rolling_quantile tests the mentioned cases too.

jreback

pls address @jaimefrio comments

jreback · 2017-05-07T13:32:25Z

doc/source/whatsnew/v0.20.1.txt

@@ -78,7 +78,7 @@ Reshaping
 Numeric
 ^^^^^^^

-
+- Bug in ``.rolling.quantile()`` which incorrectly used different defaults than Series.quantile() and DataFrame.quantile()


move to 0.21.0

guillemborrell

Please, check if all comments have been successfully addressed.

jaimefrio

I think this is very close to being ready, just a couple of nitpicks, and a suggestion for future improvements, but should be mostly ready to go.

jaimefrio · 2017-05-09T08:36:30Z

pandas/_libs/window.pyx

@@ -1348,6 +1348,7 @@ def roll_quantile(ndarray[float64_t, cast=True] input, int64_t win,
        bint is_variable
        ndarray[int64_t] start, end
        ndarray[double_t] output
+        double vlow, vhigh

    if quantile < 0.0 or quantile > 1.0:


The code below now relies on 0.0 and 1.0 being filtered by the Python wrapper, doesn't it? We probably should make that explicit here by changing < and > to <= and >=.

Just wanted to note that this line was not altered by my patch

Yes, but your patch does alter the valid inputs, and quantile == 1.0 is no longer a valid one. It's more of a cosmetic thing, because the Python wrapper never calls this with quantile=1.0, but I think it is still worth making the change.

jaimefrio · 2017-05-09T08:41:00Z

pandas/_libs/window.pyx

+            else:
+                vlow = skiplist.get(idx)
+                vhigh = skiplist.get(idx + 1)
+                output[i] = vlow + (vhigh - vlow) * \


Very minor nitpick: there seems to be no other occurrence of \ anywhere in this file. Can someone more familiar with Pandas style requirements comment on whether this is OK, or implicit line continuation inside parentheses is preferred?

that's fine, or you can use (). and break it at an operator.

jaimefrio · 2017-05-09T09:01:49Z

pandas/_libs/window.pyx

+            # Interpolated quantile
+            else:
+                vlow = skiplist.get(idx)
+                vhigh = skiplist.get(idx + 1)


Hadn't realized this before: skiplist.get is an O(log win) operation which we now have to perform twice. We also do a skiplist.insert and a skiplist.remove, which are also O(log win), and probably more expensive than skiplist.get, but a pessimistic estimation says the performance of this function will go down by 25%.

I think there are two things to do here:

quantify that slow down by running a couple of benchmarks with and without this PR, and leave a record of the results for further reference.

if the slowdown is significant, we could gain the speed back by doing some changes to the skiplist internals: when the first index is fetched, getting the next one is trivially simple and cheap, so we could add a .get_two() method to IndexableSkiplist and use it here. I think that would be work for another PR, but creating an issue for tracking based on the results of the benchmarks should be part of merging this.

I ran some very simple performance tests. The new version is indeed 25% slower.

New

In [1]: import pandas In [2]: pandas.__version__ Out[2]: '0.20.0+19.g36db9bdaf' In [3]: import numpy as np In [4]: df = pandas.DataFrame({'a': np.random.random(1000000)}) In [5]: %timeit df.a.rolling(10).quantile(0.5) 1 loop, best of 3: 1.78 s per loop In [6]: %timeit df.a.rolling(10).median() 1 loop, best of 3: 460 ms per loop

Old

In [1]: import pandas In [2]: pandas.__version__ Out[2]: '0.20.1' In [3]: import numpy as np In [4]: df = pandas.DataFrame({'a': np.random.random(1000000)}) In [5]: %timeit df.a.rolling(10).quantile(0.5) 1 loop, best of 3: 1.4 s per loop In [6]: %timeit df.a.rolling(10).median() 1 loop, best of 3: 451 ms per loop

YMMV, of course.

Thanks for doing this! Seeing this, there is a more obvious approach to speeding this in a future PR: use the C implemented skiplist that median uses, instead of the Cython IndexableSkiplist used by quantile. But that's clearly a different PR.

@jaimefrio the issue is that for median you are only doing a single calculation. when doing many calculations (like here) a skip list is far faster. The actual impl of the skiplist could be improved a lot though (it has python objects inside it).

guillemborrell

I think that this last commit successfully addresses all reviews.

jaimefrio · 2017-05-10T09:41:16Z

It think it is fully ready to go now. Thanks Guillem!

jreback · 2017-05-10T09:42:52Z

do we have an asv for this (or for window functions generally)?

would be straightforward to add if not

jreback · 2017-05-10T09:44:59Z

doc/source/whatsnew/v0.21.0.txt

@@ -107,6 +107,7 @@ Reshaping
 Numeric
 ^^^^^^^

+- Bug in ``.rolling.quantile()`` which incorrectly used different defaults than Series.quantile() and DataFrame.quantile()


move to rolling section

guillemborrell · 2017-05-10T11:39:12Z

I hope it is all set now.

@jreback I looked at the asv_bench folder, and It seems that there are no benchmarks for window functions. I assume that your suggestion is to add them in another PR.

jreback · 2017-05-10T11:40:42Z

@guillemborrell actually would be great to add them here. just add a new file (copy existing one) and edit.

guillemborrell · 2017-05-11T13:36:41Z

I'll write some benchmarks then, but I won't be able to do it until next weekend. When does v 0.21 freeze?

jreback · 2017-05-11T13:45:12Z

@guillemborrell just released 0.20.1, so 0.21 will be a few months.

guillemborrell · 2017-05-23T13:55:53Z

@jreback I have added a benchmark file that tests the methods of rolling windows. I have added small and large windows for all tests despite they are only relevant for quantiles. Please, take a look if those benchmarks are good enough.

jreback · 2017-06-10T19:06:39Z

can you show the benchmark results?

guillemborrell · 2017-06-12T14:06:00Z

Sure. This is for pandas 0.20.1

· Discovering benchmarks
· Running 48 total benchmarks (1 commits * 1 environments * 48 benchmarks)
[  0.00%] ·· Building for existing-py_usr_bin_python
[  0.00%] ·· Benchmarking existing-py_usr_bin_python
[  2.08%] ··· Running rolling.DataframeRolling.time_rolling_corr                    2.23s
[  4.17%] ··· Running rolling.DataframeRolling.time_rolling_count                  4.43ms
[  6.25%] ··· Running rolling.DataframeRolling.time_rolling_count_l                4.35ms
[  8.33%] ··· Running rolling.DataframeRolling.time_rolling_cov                     2.29s
[ 10.42%] ··· Running rolling.DataframeRolling.time_rolling_kurt                   3.63ms
[ 12.50%] ··· Running rolling.DataframeRolling.time_rolling_kurt_l                 4.34ms
[ 14.58%] ··· Running rolling.DataframeRolling.time_rolling_max                    3.59ms
[ 16.67%] ··· Running rolling.DataframeRolling.time_rolling_max_l                  3.81ms
[ 18.75%] ··· Running rolling.DataframeRolling.time_rolling_median                 2.73ms
[ 20.83%] ··· Running rolling.DataframeRolling.time_rolling_median_l               2.66ms
[ 22.92%] ··· Running rolling.DataframeRolling.time_rolling_min                    3.55ms
[ 25.00%] ··· Running rolling.DataframeRolling.time_rolling_min_l                  3.84ms
[ 27.08%] ··· Running rolling.DataframeRolling.time_rolling_quantile_0           110.07ms
[ 29.17%] ··· Running rolling.DataframeRolling.time_rolling_quantile_0_l         234.01ms
[ 31.25%] ··· Running rolling.DataframeRolling.time_rolling_quantile_1           129.11ms
[ 33.33%] ··· Running rolling.DataframeRolling.time_rolling_quantile_1_l         290.30ms
[ 35.42%] ··· Running rolling.DataframeRolling.time_rolling_quantile_median      123.17ms
[ 37.50%] ··· Running rolling.DataframeRolling.time_rolling_quantile_median_l    262.23ms
[ 39.58%] ··· Running rolling.DataframeRolling.time_rolling_skew                   5.45ms
[ 41.67%] ··· Running rolling.DataframeRolling.time_rolling_skew_l                 3.93ms
[ 43.75%] ··· Running rolling.DataframeRolling.time_rolling_std                    4.63ms
[ 45.83%] ··· Running rolling.DataframeRolling.time_rolling_std_l                  3.08ms
[ 47.92%] ··· Running rolling.DataframeRolling.time_rolling_sum                    2.87ms
[ 50.00%] ··· Running rolling.DataframeRolling.time_rolling_sum_l                  2.59ms
[ 52.08%] ··· Running rolling.SeriesRolling.time_rolling_corr                      6.35ms
[ 54.17%] ··· Running rolling.SeriesRolling.time_rolling_count                     7.68ms
[ 56.25%] ··· Running rolling.SeriesRolling.time_rolling_count_l                   7.37ms
[ 58.33%] ··· Running rolling.SeriesRolling.time_rolling_cov                       4.78ms
[ 60.42%] ··· Running rolling.SeriesRolling.time_rolling_kurt                      5.04ms
[ 62.50%] ··· Running rolling.SeriesRolling.time_rolling_kurt_l                    4.87ms
[ 64.58%] ··· Running rolling.SeriesRolling.time_rolling_max                       4.76ms
[ 66.67%] ··· Running rolling.SeriesRolling.time_rolling_max_l                     4.85ms
[ 68.75%] ··· Running rolling.SeriesRolling.time_rolling_median                    3.89ms
[ 70.83%] ··· Running rolling.SeriesRolling.time_rolling_median_l                  3.87ms
[ 72.92%] ··· Running rolling.SeriesRolling.time_rolling_min                       4.67ms
[ 75.00%] ··· Running rolling.SeriesRolling.time_rolling_min_l                     4.89ms
[ 77.08%] ··· Running rolling.SeriesRolling.time_rolling_quantile_0              114.80ms
[ 79.17%] ··· Running rolling.SeriesRolling.time_rolling_quantile_0_l            223.83ms
[ 81.25%] ··· Running rolling.SeriesRolling.time_rolling_quantile_1              140.83ms
[ 83.33%] ··· Running rolling.SeriesRolling.time_rolling_quantile_1_l            274.94ms
[ 85.42%] ··· Running rolling.SeriesRolling.time_rolling_quantile_median         125.02ms
[ 87.50%] ··· Running rolling.SeriesRolling.time_rolling_quantile_median_l       263.54ms
[ 89.58%] ··· Running rolling.SeriesRolling.time_rolling_skew                      4.77ms
[ 91.67%] ··· Running rolling.SeriesRolling.time_rolling_skew_l                    4.59ms
[ 93.75%] ··· Running rolling.SeriesRolling.time_rolling_std                       4.54ms
[ 95.83%] ··· Running rolling.SeriesRolling.time_rolling_std_l                     9.10ms
[ 97.92%] ··· Running rolling.SeriesRolling.time_rolling_sum                       3.74ms
[100.00%] ··· Running rolling.SeriesRolling.time_rolling_sum_l                     3.79ms

And the benchmark from this PR.

· Discovering benchmarks
· Running 48 total benchmarks (1 commits * 1 environments * 48 benchmarks)
[  0.00%] ·· Building for existing-py_usr_bin_python
[  0.00%] ·· Benchmarking existing-py_usr_bin_python
[  2.08%] ··· Running rolling.DataframeRolling.time_rolling_corr                    2.22s
[  4.17%] ··· Running rolling.DataframeRolling.time_rolling_count                  4.28ms
[  6.25%] ··· Running rolling.DataframeRolling.time_rolling_count_l                4.31ms
[  8.33%] ··· Running rolling.DataframeRolling.time_rolling_cov                     2.24s
[ 10.42%] ··· Running rolling.DataframeRolling.time_rolling_kurt                   3.53ms
[ 12.50%] ··· Running rolling.DataframeRolling.time_rolling_kurt_l                 3.48ms
[ 14.58%] ··· Running rolling.DataframeRolling.time_rolling_max                    3.70ms
[ 16.67%] ··· Running rolling.DataframeRolling.time_rolling_max_l                  3.65ms
[ 18.75%] ··· Running rolling.DataframeRolling.time_rolling_median                 2.59ms
[ 20.83%] ··· Running rolling.DataframeRolling.time_rolling_median_l               2.58ms
[ 22.92%] ··· Running rolling.DataframeRolling.time_rolling_min                    3.52ms
[ 25.00%] ··· Running rolling.DataframeRolling.time_rolling_min_l                  3.67ms
[ 27.08%] ··· Running rolling.DataframeRolling.time_rolling_quantile_0           114.64ms
[ 29.17%] ··· Running rolling.DataframeRolling.time_rolling_quantile_0_l         215.85ms
[ 31.25%] ··· Running rolling.DataframeRolling.time_rolling_quantile_1           139.79ms
[ 33.33%] ··· Running rolling.DataframeRolling.time_rolling_quantile_1_l         337.24ms
[ 35.42%] ··· Running rolling.DataframeRolling.time_rolling_quantile_median      157.48ms
[ 37.50%] ··· Running rolling.DataframeRolling.time_rolling_quantile_median_l    268.86ms
[ 39.58%] ··· Running rolling.DataframeRolling.time_rolling_skew                   3.50ms
[ 41.67%] ··· Running rolling.DataframeRolling.time_rolling_skew_l                 3.68ms
[ 43.75%] ··· Running rolling.DataframeRolling.time_rolling_std                    3.37ms
[ 45.83%] ··· Running rolling.DataframeRolling.time_rolling_std_l                  5.29ms
[ 47.92%] ··· Running rolling.DataframeRolling.time_rolling_sum                    2.65ms
[ 50.00%] ··· Running rolling.DataframeRolling.time_rolling_sum_l                  2.55ms
[ 52.08%] ··· Running rolling.SeriesRolling.time_rolling_corr                      6.54ms
[ 54.17%] ··· Running rolling.SeriesRolling.time_rolling_count                     8.18ms
[ 56.25%] ··· Running rolling.SeriesRolling.time_rolling_count_l                   7.78ms
[ 58.33%] ··· Running rolling.SeriesRolling.time_rolling_cov                       4.79ms
[ 60.42%] ··· Running rolling.SeriesRolling.time_rolling_kurt                      6.16ms
[ 62.50%] ··· Running rolling.SeriesRolling.time_rolling_kurt_l                    5.02ms
[ 64.58%] ··· Running rolling.SeriesRolling.time_rolling_max                       9.15ms
[ 66.67%] ··· Running rolling.SeriesRolling.time_rolling_max_l                     5.31ms
[ 68.75%] ··· Running rolling.SeriesRolling.time_rolling_median                    4.27ms
[ 70.83%] ··· Running rolling.SeriesRolling.time_rolling_median_l                  4.30ms
[ 72.92%] ··· Running rolling.SeriesRolling.time_rolling_min                       6.82ms
[ 75.00%] ··· Running rolling.SeriesRolling.time_rolling_min_l                     5.69ms
[ 77.08%] ··· Running rolling.SeriesRolling.time_rolling_quantile_0              128.50ms
[ 79.17%] ··· Running rolling.SeriesRolling.time_rolling_quantile_0_l            252.35ms
[ 81.25%] ··· Running rolling.SeriesRolling.time_rolling_quantile_1              134.18ms
[ 83.33%] ··· Running rolling.SeriesRolling.time_rolling_quantile_1_l            280.08ms
[ 85.42%] ··· Running rolling.SeriesRolling.time_rolling_quantile_median         118.44ms
[ 87.50%] ··· Running rolling.SeriesRolling.time_rolling_quantile_median_l       276.01ms
[ 89.58%] ··· Running rolling.SeriesRolling.time_rolling_skew                      5.27ms
[ 91.67%] ··· Running rolling.SeriesRolling.time_rolling_skew_l                    5.01ms
[ 93.75%] ··· Running rolling.SeriesRolling.time_rolling_std                       7.04ms
[ 95.83%] ··· Running rolling.SeriesRolling.time_rolling_std_l                     5.39ms
[ 97.92%] ··· Running rolling.SeriesRolling.time_rolling_sum                       4.39ms
[100.00%] ··· Running rolling.SeriesRolling.time_rolling_sum_l                     4.23ms

jreback · 2017-07-07T10:37:30Z

did the benchmarks show a diff? also pls rebase and push again just to confirm tests still working.

guillemborrell · 2017-07-07T12:13:33Z

No significant changes other than rolling windows for quantiles, that are about 25% slower, but YMMV.

jreback · 2017-07-07T12:16:01Z

looks like you picked up some other changes, do

git rebase -i upstream/master
git push <yourbranchname> <yourfork> -r

jreback

doc comments. ping on green.

jreback · 2017-07-07T14:29:13Z

doc/source/whatsnew/v0.21.0.txt

 - Bug in ``infer_freq`` causing indices with 2-day gaps during the working week to be wrongly inferred as business daily (:issue:`16624`)
+- Bug in ``.rolling.quantile()`` which incorrectly used different defaults than Series.quantile() and DataFrame.quantile()


.rolling(...).quantile() and use :func:Series.quantile and :func:DataFrame.quantile

add the issue number #9413 and #16211

jreback · 2017-07-07T14:30:46Z

pandas/tests/test_window.py

@@ -1138,6 +1149,28 @@ def alt(x):

            self._check_moment_func(f, alt, name='quantile', quantile=q)

+    def test_rolling_quantile_np_percentile(self):
+        # #9413


add a 1-liner to both functions explaining what you are testing (e.g. the nature of the bug)

guillemborrell · 2017-07-08T09:11:40Z

It seems that app appveyor failed, but not due to a test. How do I proceed?

jreback · 2017-07-08T17:24:21Z

i restarted

jaimefrio · 2017-07-09T16:43:19Z

It's all green now.

guillemborrell · 2017-07-10T07:16:03Z

Thanks for pinging @jaimefrio. I was off-screen for a couple of days.

jreback · 2017-07-10T10:15:11Z

thanks!

@TomAugspurger

* consolidated the duplicate definitions of NA values (in parsers & IO) (pandas-dev#16589) * GH15943 Fixed defaults for compression in HDF5 (pandas-dev#16355) * DOC: add header=None to read_excel docstring (pandas-dev#16689) * TST: Test against python-dateutil master (pandas-dev#16648) * BUG: .iloc[:] and .loc[:] return a copy of the original object pandas-dev#13873 (pandas-dev#16443) closes pandas-dev#13873 * TST: Add test of building frame from named Series and columns (pandas-dev#9232) (pandas-dev#16700) * DOC: fix wrongly placed versionadded (pandas-dev#16702) * DOC: pin sphinx to version 1.5 (pandas-dev#16704) * CI: restore np 113 in ci builds (pandas-dev#16656) * Revert "BLD: fix numpy on 3.6 build as 1.13 was released but no deps are built for it (pandas-dev#16633)" This reverts commit dfebd8a. closes pandas-dev#16634 * BUG: Fix regression for RGB(A) color arguments (pandas-dev#16701) * Add test * Pass tuples that are RGB or RGBA like in list * Update what's new * change whatsnew to reflect regression fix * Add test for RGBA as well * CI: pin jemalloc=4.4.0 (pandas-dev#16727) * MAINT: Drop Categorical.order & sort (pandas-dev#16728) Deprecated back in 0.18.1 xref pandas-devgh-12882 * Fix reading Series with read_hdf (pandas-dev#16610) * Added test to reproduce issue pandas-dev#16583 * Fix pandas-dev#16583 by adding an explicit `mode` argument to `read_hdf` kwargs which are meant for the opening of the HDFStore should be filtered out before passing the remaining kwargs to the `select` function to load the data. * Noted fix for pandas-dev#16583 in WhatsNew * DOC: typo (pandas-dev#16733) * whatsnew v0.21.0.txt typos (pandas-dev#16742) * whatsnew v0.20.3 edits (pandas-dev#16743) * BUG: do not raise UnsortedIndexError if sorting is not required closes pandas-dev#16734 Author: Pietro Battiston <me@pietrobattiston.it> This patch had conflicts when merged, resolved by Committer: Jeff Reback <jeff.reback@twosigma.com> Closes pandas-dev#16736 from toobaz/index_what_you_can and squashes the following commits: f77e2b3 [Pietro Battiston] BUG: do not raise UnsortedIndexError if sorting is not required * DOC: whatsnew typos * Test for pandas-dev#16726. unittest that ensures datetime is understood (pandas-dev#16744) * Test for pandas-dev#16726. unittest that ensures datetime is understood * Corrected the test as suggested by @TomAugspurger * Fixed flake8 errors and warnings * DOC: some rst fixes (pandas-dev#16763) * DOC: Update Sphinx Deprecated Directive (pandas-dev#16512) * MAINT: Drop Index.sym_diff (pandas-dev#16760) Deprecated in 0.18.1 xref pandas-devgh-12591, pandas-devgh-12594 * MAINT: Drop pd.options.display.mpl_style (pandas-dev#16761) Deprecated in 0.18.0 xref pandas-devgh-12190 * DOC: remove section on Panel4D support in HDF io (pandas-dev#16783) * DOC: add section on data validation and library engarde (pandas-dev#16758) * TST: register slow marker (pandas-dev#16797) * TST: register slow marker * Update setup.cfg * BUG: Load data from a CategoricalIndex for dtype comparison, closes #… (pandas-dev#16738) * BUG: Load data from a CategoricalIndex for dtype comparison, closes pandas-dev#16627 * Enable is_dtype_equal on CategoricalIndex, fixed some doc typos, added ordered CategoricalIndex test * Flake8 windows suggestion * Fixed some documentation/formatting issues, clarified the purpose of the test case. * Bug in pd.merge() when merge/join with multiple categorical columns (pandas-dev#16786) closes pandas-dev#16767 * BUG: Fix read of py3 PeriodIndex DataFrame HDF made in py2 (pandas-dev#16781) (pandas-dev#16790) In Python3, reading a DataFrame with a PeriodIndex from an HDF file created in Python2 would incorrectly return a DataFrame with an Int64Index. * BUG: Fix Series doesn't work in pd.astype(). Now treat Series as dict. (pandas-dev#16725) * FIX: Allow aggregate to return dictionaries again pandas-dev#16741 (pandas-dev#16752) * BUG: fix to_latex bold_rows option (pandas-dev#16708) * Revert "CI: pin jemalloc=4.4.0 (pandas-dev#16727)" (pandas-dev#16731) This reverts commit 09d8c22. * CI: use dist/trusty rather than os/linux (pandas-dev#16806) closes pandas-dev#16730 * TST: Verify columns entirely below chop_threshold still print (pandas-dev#6839) (pandas-dev#16809) * BUG: clip dataframe column-wise pandas-dev#15390 (pandas-dev#16504) * TST: Verify that positional shifting works with duplicate columns (pandas-dev#9092) (pandas-dev#16810) * BUG: render dataframe as html do not produce duplicate element id's (pandas-dev#16780) (pandas-dev#16801) * BUG: when rendering dataframe as html do not produce duplicate element id's pandas-dev#16780 * CLN: removing spaces in code causes pylint check to fail * DOC: moved whatsnew comment to 0.20.3 release from 0.21.0 * fix BUG: ValueError when performing rolling covariance on multi indexed DataFrame (pandas-dev#16814) * fix multi index names * fix line length to pep8 * added what's new entry and reference issue number in test * Update test_multi.py * Update v0.20.3.txt * BUG: rolling.cov with multi-index columns should presever the MI (pandas-dev#16825) xref pandas-dev#16814 * use network decorator on additional tests (pandas-dev#16824) * BUG: TimedeltaIndex raising ValueError when slice indexing (pandas-dev#16637) (pandas-dev#16638) * Bug issue 16819 Index.get_indexer_not_unique inconsistent return types vs get_indexer (pandas-dev#16826) * TST: Verify that float columns stay float after pivot (pandas-dev#7142) (pandas-dev#16815) * BUG/MAINT: Change default of inplace to False in pd.eval (pandas-dev#16732) * BUG: kind parameter on categorical argsort (pandas-dev#16834) * DOC: Updated cookbook to show usage of Grouper instead of TimeGrouper… (pandas-dev#16794) * BUG: allow empty multiindex (fixes .isin regression, GH16777) (pandas-dev#16782) * BUG: fix missing sort keyword for PeriodIndex.join (pandas-dev#16586) * COMPAT: 32-bit compat for testing of indexers (pandas-dev#16849) xref pandas-dev#16826 * BUG: fix infer frequency for business daily (pandas-dev#16683) * DOC: Whatsnew updates (pandas-dev#16853) [ci skip] * TST/PKG: Move test HDF5 file to legacy (pandas-dev#16856) It wasn't being picked up in our package data otherwise * COMPAT: moar 32-bit compat for testing of indexers (pandas-dev#16861) xref pandas-dev#16826 * MAINT: Drop the get_offset_name method (pandas-dev#16863) Deprecated since 0.18.0 xref pandas-devgh-11834 * DOC: Fix missing parentheses in documentation (pandas-dev#16862) * BUG: rolling.quantile does not return an interpolated result (pandas-dev#16247) * ENH - Modify Dataframe.select_dtypes to accept scalar values (pandas-dev#16860) * COMPAT: moar 32-bit compat for testing of indexers (pandas-dev#16869) xref pandas-dev#16826 * Confirm that select was *not* clearer in 0.12 (pandas-dev#16878) * Added tests for _get_dtype (pandas-dev#16845) * BUG: Series.isin fails or categoricals (pandas-dev#16858) * COMPAT with dateutil 2.6.1, fixed ambiguous tz dst behavior (pandas-dev#16880) * fix wrongly named method (pandas-dev#16881) * TST/PKG: Removed pandas.util.testing.slow definition (pandas-dev#16852) * MAINT: Remove unused mock import (pandas-dev#16908) We import it, set it as an attribute, and then don't use it. * Let _get_dtype accept Categoricals and CategoricalIndex (pandas-dev#16887) * Fixes for pandas-dev#16896(TimedeltaIndex indexing regression for strings) (pandas-dev#16907) * Fix for pandas-dev#16909(DeltatimeIndex.get_loc is not working on np.deltatime64 data type) (pandas-dev#16912) * DOC: Recommend sphinx 1.5 for now (pandas-dev#16929) For the SciPy sprint tomorrow, until the cause of the doc-building slowdown is fully identified. * BUG: Allow value labels to be read with iterator (pandas-dev#16926) All value labels to be read before the iterator has been used Fix issue where categorical data was incorrectly reformatted when write_index was False closes pandas-dev#16923 * DOC: Update flake8 command instructions (pandas-dev#16919) * TST: Don't assert that a bug exists in numpy (pandas-dev#16940) Better to ignore the warning from the bug, rather than assert the bug is still there After this change, numpy/numpy#9412 _could_ be backported to fix the bug * CI: add .pep8speakes.yml * CLN16668: remove OrderedDefaultDict (pandas-dev#16939) * Change "pls" to "please" in error message (pandas-dev#16947) * BUG: MultiIndex sort with ascending as list (pandas-dev#16937) * DOC: Improving docstring of pop method (pandas-dev#16416) (pandas-dev#16520) * PEP8 * WARN: add stacklevel to to_dict() UserWarning (pandas-dev#16927) (pandas-dev#16936) * ERR: add stacklevel to to_dict() UserWarning (pandas-dev#16927) * TST: Add warning testing to to_dict() * Fix warning assertion on to_dict() test * Add github issue to documentation on to_dict() warning test * CI: fix pep8speaks .yml file * DOC: whatsnew 0.21.0 edits * CI: disable codecov reporting * MAINT: Move series.remove_na to core.dtypes.missing.remove_na_arraylike Closes pandas-devgh-16935 * Support non unique period indexes on join and merge operations (pandas-dev#16949) * Support non unique period indexes on join and merge operations * Add frame assertion on tests and release notes * Explicitly use dtype int64 on arange * BUG: Set secondary axis font size for `secondary_y` during plotting The parameter was not being respected for `secondary_y`. Closes pandas-devgh-12565 * DOC: more whatsnew fixes * DOC: Reset index examples closes pandas-dev#16416 Author: aernlund <awe220@nyumc.org> Closes pandas-dev#16967 from aernlund/reset_index_docs and squashes the following commits: 3c6a4b6 [aernlund] DOC: added examples to reset_index 4838155 [aernlund] DOC: added examples to reset_index 2a51e2b [aernlund] DOC: added examples to reset_index * channel from pandas to conda-forge (pandas-dev#16966) * BUG: coercing of bools in groupby transform (pandas-dev#16895) * DOC: misspelling in DatetimeIndex.indexer_between_time [CI skip] (pandas-dev#16963) * CLN: some residual code removed, xref to pandas-dev#16761 (pandas-dev#16974) * ENH: Create a 'Y' alias for date_range yearly frequency Closes pandas-devgh-9313 * Revert "ENH: Create a 'Y' alias for date_range yearly frequency" (pandas-dev#16976) This reverts commit 9c096d2, as it was prematurely made. * DOC: behavior when slicing with missing bounds (pandas-dev#16932) closes pandas-dev#16917 * TST: Add test for sub-char in read_csv (pandas-dev#16977) Closes pandas-devgh-16893. * DEPR: deprecate html.border option (pandas-dev#16970) * DOC: document convention argument for resample() (pandas-dev#16965) * DOC: document convention argument for resample() * DOC: Clarify 'it' in aggregate doc (pandas-dev#16989) Closes pandas-devgh-16988. * CLN/COMPAT: for various py2/py3 in doc/bench scripts (pandas-dev#16984) * PERF: SparseDataFrame._init_dict uses intermediary dict, not DataFrame (pandas-dev#16883) Closes pandas-devgh-16773. * MAINT: Drop line_width and height from options (pandas-dev#16993) Deprecated since 0.11 and 0.12 respectively. * COMPAT: Add back remove_na for seaborn (pandas-dev#16992) Closes pandas-devgh-16971. * COMPAT: np.full not available in all versions, xref pandas-dev#16773 (pandas-dev#17000) * DOC, TST: Clarify whitespace behavior in read_fwf documentation (pandas-dev#16950) Closes pandas-devgh-16772 * API: add infer_objects for soft conversions (pandas-dev#16915) * API: add infer_objects for soft conversions * doc fixups * fixups * doc * BUG: np.inf now causes Index to upcast from int to float (pandas-dev#16996) Closes pandas-devgh-16957. * DOC: Make highlight functions match documentation (pandas-dev#16999) Closes pandas-devgh-16998. * BUG: Large object array isin closes pandas-dev#16012 Author: Morgan Stuart <morgansstuart243@gmail.com> Closes pandas-dev#16969 from Morgan243/large_array_isin and squashes the following commits: 31cb4b3 [Morgan Stuart] Removed unneeded details from whatsnew description 4b59745 [Morgan Stuart] Linting errors; additional test clarification 186607b [Morgan Stuart] BUG pandas-dev#16012 - fix isin for large object arrays * BUG: reindex would throw when a categorical index was empty pandas-dev#16770 closes pandas-dev#16770 Author: ri938 <r_irv938@hotmail.com> Author: Jeff Reback <jeff@reback.net> Author: Tuan <tuan.d.tran@hotmail.com> Author: Forbidden Donut <forbdonut@gmail.com> This patch had conflicts when merged, resolved by Committer: Jeff Reback <jeff@reback.net> Closes pandas-dev#16820 from ri938/bug_issue16770 and squashes the following commits: 0e2d315 [ri938] Merge branch 'master' into bug_issue16770 9802288 [ri938] Update v0.20.3.txt 1f2865e [ri938] Update v0.20.3.txt 83fd749 [ri938] Update v0.20.3.txt eab3192 [ri938] Merge branch 'master' into bug_issue16770 7acc09f [ri938] Minor correction to previous submit 6e8f1b3 [ri938] Minor corrections to previous submit (pandas-dev#16820) 9ed80f0 [ri938] Bring documentation into line with master branch. 26e1a60 [ri938] Move documentation of change to the next major release 0.21.0 59b17cd [Jeff Reback] BUG: rolling.cov with multi-index columns should presever the MI (pandas-dev#16825) 5362447 [Tuan] fix BUG: ValueError when performing rolling covariance on multi indexed DataFrame (pandas-dev#16814) 800b40d [ri938] BUG: render dataframe as html do not produce duplicate element id's (pandas-dev#16780) (pandas-dev#16801) a725fbf [Forbidden Donut] BUG: Fix read of py3 PeriodIndex DataFrame HDF made in py2 (pandas-dev#16781) (pandas-dev#16790) 8f8e3d6 [ri938] TST: register slow marker (pandas-dev#16797) 0645868 [ri938] Add backticks in documentation 0a20024 [ri938] Minor correction to previous submit 69454ec [ri938] Minor corrections to previous submit (pandas-dev#16820) 3092bbc [ri938] BUG: reindex would throw when a categorical index was empty pandas-dev#16770 * BUG: Don't with empty Series for .isin (pandas-dev#17006) Empty Series initializes to float64, even when the data type is object for .isin, leading to an error with membership. Closes pandas-devgh-16991. * ENH: Use 'Y' as an alias for end of year (pandas-dev#16978) Closes pandas-devgh-9313 Redo of pandas-devgh-16958 * DOC: infer_objects doc fixup (pandas-dev#17018) * Fixes SparseSeries initiated with dictionary raising AttributeError (pandas-dev#16960) * DOC: Improving docstring of reset_index method (pandas-dev#16416) (pandas-dev#16975) * DOC: add warning to append about inefficiency (pandas-dev#17017) * DOC : Remove redundant backtick (pandas-dev#17025) * DOC: Document business frequency aliases (pandas-dev#17028) Follow-up to pandas-devgh-16978. * DOC: Fix double back-tick in 'Reshaping by Melt' section (pandas-dev#17030) See current stable docs for the issue: https://pandas.pydata.org/pandas-docs/stable/reshaping.html#reshaping-by-melt The double ` is causing the entire paragraph to be fixed width until the next double `. This commit removes the extra "`" * Define DataFrame plot methods in DataFrame (pandas-dev#17020) * CLN: move safe_sort from core.algorithms to core.sorting (pandas-dev#17034) COMPAT: safe_sort will only coerce list-likes to object, not a numpy string type xref: pandas-dev#17003 (comment) * DOC: Fixed Minor Typo (pandas-dev#17043) Cocumentation to Documentation * BUG: do not cast ints to floats if inputs o crosstab are not aligned (pandas-dev#17011) closes pandas-dev#17005 * BUG in merging categorical dates closes pandas-dev#16900 Author: Dave Willmer <dave.willmer@gmail.com> This patch had conflicts when merged, resolved by Committer: Jeff Reback <jeff@reback.net> Closes pandas-dev#16986 from dwillmer/cat_fix and squashes the following commits: 1ea1977 [Dave Willmer] Minor tweaks + comment 21a35a0 [Dave Willmer] Merge branch 'cat_fix' of https://github.com/dwillmer/pandas into cat_fix 04d5404 [Dave Willmer] Update tests 3cc5c24 [Dave Willmer] Merge branch 'master' into cat_fix 5e8e23b [Dave Willmer] Add whatsnew item b82d117 [Dave Willmer] Lint fixes a81933d [Dave Willmer] Remove unused import 218da66 [Dave Willmer] Generic solution to categorical problem 48e7163 [Dave Willmer] Test inner join 8843c10 [Dave Willmer] Fix TypeError when merging categorical dates * BUG: __setitem__ with a tuple induces NaN with a tz-aware DatetimeIndex (pandas-dev#16889) (pandas-dev#16897) * Added test for _get_dtype_type. (pandas-dev#16899) * BUG/API: dtype inconsistencies in .where / .setitem / .putmask / .fillna (pandas-dev#16821) * CLN/BUG: fix ndarray assignment may cause unexpected cast supersedes pandas-dev#14145 closes pandas-dev#14001 * API: This fixes a number of inconsistencies and API issues w.r.t. dtype conversions. This is a reprise of pandas-dev#14145 & pandas-dev#16408. This removes some code from the core structures & pushes it to internals, where the primitives are made more consistent. This should all us to be a bit more consistent for pandas2 type things. closes pandas-dev#16402 supersedes pandas-dev#14145 closes pandas-dev#14001 CLN: remove uneeded code in internals; use split_and_operate when possible * BUG: Improved thread safety for read_html() GH16928 (pandas-dev#16930) * Fixed 'add_methods' when the 'select' argument is specified. (pandas-dev#17045) * TST: Fix error message check in np.argsort comparision (pandas-dev#17051) Closes pandas-devgh-17046. * TST: Move some Series ctor tests to SharedWithSparse (pandas-dev#17050) * BUG: Made SparseDataFrame.fillna() fill all NaNs A continuation of pandas-dev#16178 closes pandas-dev#16112 closes pandas-dev#16178 Author: Kernc <kerncece@gmail.com> Author: keitakurita <kris337jbn@yahoo.co.jp> This patch had conflicts when merged, resolved by Committer: Jeff Reback <jeff@reback.net> Closes pandas-dev#16892 from kernc/sparse-fillna and squashes the following commits: c1cd33e [Kernc] fixup! BUG: Made SparseDataFrame.fillna() fill all NaNs 2974232 [Kernc] fixup! BUG: Made SparseDataFrame.fillna() fill all NaNs 4bc01a1 [keitakurita] BUG: Made SparseDataFrame.fillna() fill all NaNs * BUG: Use size_t to avoid array index overflow; add missing malloc of error_msg Fix a few locations where a parser's `error_msg` buffer is written to without having been previously allocated. This manifested as a double free during exception handling code making use of the `error_msg`. Additionally, use `size_t/ssize_t` where array indices or lengths will be stored. Previously, int32_t was used and would overflow on columns with very large amounts of data (i.e. greater than INTMAX bytes). xref pandas-dev#14696 closes pandas-dev#16798 Author: Jeff Knupp <jeff.knupp@enigma.com> Author: Jeff Knupp <jeff@jeffknupp.com> Closes pandas-dev#17040 from jeffknupp/16790-core-on-large-csv and squashes the following commits: 6a1ba23 [Jeff Knupp] Clear up prose a5d5677 [Jeff Knupp] Fix linting issues 4380c53 [Jeff Knupp] Fix linting issues 7b1cd8d [Jeff Knupp] Fix linting issues e3cb9c1 [Jeff Knupp] Add unit test plus '--high-memory' option, *off by default*. 2ab4971 [Jeff Knupp] Remove debugging code 2930eaa [Jeff Knupp] Fix line length to conform to linter rules e4dfd19 [Jeff Knupp] Revert printf format strings; fix more comment alignment 3171674 [Jeff Knupp] Fix some leftover size_t references 0985cf3 [Jeff Knupp] Remove debugging code; fix type cast 669d99b [Jeff Knupp] Fix linting errors re: line length 1f24847 [Jeff Knupp] Fix comment alignment; add whatsnew entry e04d12a [Jeff Knupp] Switch to use int64_t rather than size_t due to portability concerns. d5c75e8 [Jeff Knupp] BUG: Use size_t to avoid array index overflow; add missing malloc of error_msg * TST: remove some test warnings in parser tests (pandas-dev#17057) TST: move highmemory test to proper location in c_parser_only xref pandas-dev#16798 * DOC: Add more examples for reset_index (pandas-dev#17055) * MAINT: Add dash in high memory message Follow-up to pandas-devgh-17057. * MAINT: kwards --> kwargs in parsers.pyx * CLN: Cleanup comments in before_install_travis.sh envars.sh doesn't exist anymore. In fact, it's been gone for awhile. * MAINT: Remove duplicate Series sort_index check Duplicate boolean validation check for sort_index in series/test_validate.py * BLD: Pin pyarrow=0.4.1 (pandas-dev#17065) Addresses pandas-devgh-17064. Also add some additional build information when calling `pd.show_versions` * ENH: provide "inplace" argument to set_axis() closes pandas-dev#14636 Author: Pietro Battiston <me@pietrobattiston.it> Closes pandas-dev#16994 from toobaz/set_axis_inplace and squashes the following commits: 8fb9d0f [Pietro Battiston] REF: adapt NDFrame.set_axis() calls to new signature 409f502 [Pietro Battiston] ENH: provide "inplace" argument to set_axis(), change signature * BUG: Fix parser field type compatability on 32-bit systems. (pandas-dev#17071) Closes pandas-devgh-17063 * COMPAT: rename isnull -> isna, notnull -> notna (pandas-dev#16972) closes pandas-dev#15001 * BUG: Thoroughly dedup columns in read_csv (pandas-dev#17060) * ENH: Add skipna parameter to infer_dtype (pandas-dev#17066) Currently defaults to False for backwards compatibility. Will default to True in the future. Closes pandas-devgh-17059. * MAINT: Remove unused variable in test_scalar.py The "expected" variable is unused at the end of a test in indexing/test_scalar.py * TST: Add tests/indexing/ and reshape/ to setup.py (pandas-dev#17076) Looks like we just forgot about them. Oops. * CI: partially revert pandas-dev#17065, un-pin pyarrow on some builds * DOC: whatsnew typos * TST: Check more error messages in tests (pandas-dev#17075) * BUG: Respect dtype when calling pivot_table with margins=True closes pandas-dev#17013 This fix actually exposed an occurrence of pandas-dev#17035 in an existing test (as well as in one I added). Author: Pietro Battiston <me@pietrobattiston.it> Closes pandas-dev#17062 from toobaz/pivot_margin_int and squashes the following commits: 2737600 [Pietro Battiston] Removed now obsolete workaround 956c4f9 [Pietro Battiston] BUG: respect dtype when calling pivot_table with margins=True * MAINT: Add missing space in parsers.pyx "2< heuristic" --> "2 < heuristic" * MAINT: Add missing paren around print statement Stray verbose print statement in parsers.pyx was bare without any parentheses. * DOC: fix typos in missing.rst xref pandas-dev#16972 * DOC: further clean-up null/na changes (pandas-dev#17113) * BUG: Allow pd.unique to accept tuple of strings (pandas-dev#17108) * BUG: Allow Series with same name with crosstab (pandas-dev#16028) Closes pandas-devgh-13279 * COMPAT: make sure use_inf_as_null is deprecated (pandas-dev#17126) closes pandas-dev#17115 * CI: bump version of xlsxwriter to 0.5.2 (pandas-dev#17142) * DOC: Clean up instructions in ISSUE_TEMPLATE (pandas-dev#17146) * Add missing space to the NotImplementedError's message for compound dtypes (pandas-dev#17140) * DOC: (de)type the return value of concat (pandas-dev#17079) (pandas-dev#17119) * BUG: Thoroughly dedup column names in read_csv (pandas-dev#17095) * DOC: Additions/updates to documentation (pandas-dev#17150) * ENH: add to/from_parquet with pyarrow & fastparquet (pandas-dev#15838) * DOC: doc typos, xref pandas-dev#15838 * TST: test for categorical index monotonicity (pandas-dev#17152) * correctly determine bottleneck version * tests for categorical index monotonicity * fix Index.is_monotonic to point to Index.is_monotonic_increasing directly * MAINT: Remove non-standard and inconsistently-used imports (pandas-dev#17085) * DOC: typos in whatsnew * DOC: whatsnew 0.21.0 fixes * BUG: Fix CSV parsing of singleton list header (pandas-dev#17090) Closes pandas-devgh-7757. * ENH: Support strings containing '%' in add_prefix/add_suffix (pandas-dev#17151) (pandas-dev#17162) * REF: repr - allow block to override values that get formatted (pandas-dev#17143) * MAINT: Drop unnecessary newlines in issue template * remove direct import of nan Author: Brock Mendel <jbrockmendel@gmail.com> Closes pandas-dev#17185 from jbrockmendel/dont_import_nan and squashes the following commits: ee260b8 [Brock Mendel] remove direct import of nan * use == to test String equality (pandas-dev#17171) * ENH: Add warning when setting into nonexistent attribute (pandas-dev#16951) closes pandas-dev#7175 closes pandas-dev#5904 * DOC: added string processing comparison with SAS (pandas-dev#16497) * CLN: remove unused get methods in internals (pandas-dev#17169) * Remove unused get methods that would raise AttributeError if called * Remove unnecessary import * TST: Partial Boolean DataFrame Indexing (pandas-dev#17186) Closes pandas-devgh-17170 * CLN: Reformat docstring for IPython fixture * Define Series.plot and Series.hist in class definition (pandas-dev#17199) * BUG: support pandas objects in iloc with old numpy versions (pandas-dev#17194) closes pandas-dev#17193 * Implement _make_accessor classmethod for PandasDelegate (pandas-dev#17166) * Create ABCDateOffset (pandas-dev#17165) * BUG: resample and apply modify the index type for empty Series (pandas-dev#17149) * DOC: Updated NDFrame.astype docs (pandas-dev#17203) * MAINT: Minor touch-ups to GitHub PULL_REQUEST_TEMPLATE (pandas-dev#17207) Remove leading space from task-list so that tasks aren't nested. * CLN: replace %s syntax with .format in core.computation (pandas-dev#17209) * Bugfix for multilevel columns with empty strings in Python 2 (pandas-dev#17099) * CLN/ASV clean-up frame stat ops benchmarks (pandas-dev#17205) * BUG: Rolling apply on DataFrame with Datetime index returns NaN (pandas-dev#17156) * CLN: Remove import exception handling (pandas-dev#17218) Imports should succeed on all versions of Python that pandas supports. * MAINT: Remove extra the's in deprecation messages (pandas-dev#17222) * DOC: Patch docs in _decorators.py * CLN: replace %s syntax with .format in pandas.util (pandas-dev#17224) * Add 'See also' sections (pandas-dev#17223) * move pivot_table doc-string to DataFrame (pandas-dev#17174) * Remove import of pandas as pd in core.window (pandas-dev#17233) * TST: Move more frame tests to SharedWithSparse (pandas-dev#17227) * REF: _get_objs_combined_axis (pandas-dev#17217) * ENH/PERF: Remove frequency inference from .dt accessor (pandas-dev#17210) * ENH/PERF: Remove frequency inference from .dt accessor * BENCH: Add DatetimeAccessor benchmark * DOC: Whatsnew * Fix apparent typo in tests (pandas-dev#17247) * COMPAT: avoid calling getsizeof() on PyPy closes pandas-dev#17228 Author: mattip <matti.picus@gmail.com> Closes pandas-dev#17229 from mattip/getsizeof-unavailable and squashes the following commits: d2623e4 [mattip] COMPAT: avoid calling getsizeof() on PyPy * CLN: replace %s syntax with .format in pandas.core.reshape (pandas-dev#17252) Replaced %s syntax with .format in pandas.core.reshape. Additionally, made some of the existing positional .format code more explicit. * ENH: Infer compression from non-string paths (pandas-dev#17206) * Fix bugs in IntervalIndex.is_non_overlapping_monotonic (pandas-dev#17238) * BUG: Fix behavior of argmax and argmin with inf (pandas-dev#16449) (pandas-dev#16449) Closes pandas-dev#13595 * CLN: Remove have_pytz (pandas-dev#17266) Closes pandas-devgh-17251 * CLN: replace %s syntax with .format in core.dtypes and core.sparse (pandas-dev#17270) * Replace imports of * with explicit imports (pandas-dev#17269) xref pandas-dev#17234 * TST: pytest deprecation warnings GH17197 (pandas-dev#17253) Test parameters with marks are updated according to the updated API of Pytest. https://docs.pytest.org/en/latest/changelog.html#pytest-3-2-0-2017-07-30 https://docs.pytest.org/en/latest/parametrize.html * Handle more date/datetime/time formats (pandas-dev#15871) * DOC: add example on json_normalize (pandas-dev#16438) * BUG: Have object dtype for empty Categorical.categories (pandas-dev#17249) * BUG: Have object dtype for empty Categorical ctor Previously we had a `Float64Index`, which is inconsistent with, e.g., the regular Index constructor. * TST: Update tests in multi for new return Previously these relied worked around the return type by wrapping list-likes in `np.array` and relying on that to cast to float. These workarounds are no longer nescessary. * TST: Update union_categorical tests This relied on `NaN` being a float and empty being a float. Not a necessary test anymore. * TST: set object dtype * CLN: replace %s syntax with .format in pandas.tseries (pandas-dev#17290) * TST: parameterize consistency tests for rolling/expanding windows (pandas-dev#17292) * FIX: define `DataFrame.items` for all versions of python (pandas-dev#17214) * PERF: Update ASV publish config (pandas-dev#17293) Stricter cutoffs for considering regressions [ci skip] * DOC: Expand docstrings for head / tail methods (pandas-dev#16941) * MAINT: Use set literal for unsupported + depr args Initializes unsupported and deprecated argument sets with set literals instead of the set constructor in pandas/io/parsers.py, as the former is slightly faster than the latter. * DOC: Add proper docstring to maybe_convert_indices Patches several spelling errors and expands current doc to a proper doc-string. * DOC: Improving docstring of take method (pandas-dev#16948) * BUG: Fixed regex in asv.conf.json (pandas-dev#17300) In pandas-dev#17293 I messed up the syntax. I used a glob instead of a regex. According to the docs at http://asv.readthedocs.io/en/latest/asv.conf.json.html#regressions-thresholds we want to use a regex. I've actually manually tested this change and verified that it works. [ci skip] * Remove unnecessary usage of _TSObject (pandas-dev#17297) * BUG: clip should handle null values closes pandas-dev#17276 Author: Michael Gasvoda <mgasvoda@mercatus.gmu.edu> Author: mgasvoda <mgasvoda01@gmail.com> Closes pandas-dev#17288 from mgasvoda/master and squashes the following commits: a1dbdf2 [mgasvoda] Merge branch 'master' into master 9333952 [Michael Gasvoda] Checking output of tests 4e0464e [Michael Gasvoda] fixing whatsnew text c442040 [Michael Gasvoda] formatting fixes 7e23678 [Michael Gasvoda] formatting updates 781ea72 [Michael Gasvoda] whatsnew entry d9627fe [Michael Gasvoda] adding clip tests 9aa0159 [Michael Gasvoda] Treating na values as none for clips * BUG: fillna returns frame when inplace=True if value is a dict (pandas-dev#16156) (pandas-dev#17279) * CLN: Index.append() refactoring (pandas-dev#16236) * DEPS: set min versions (pandas-dev#17002) closes pandas-dev#15206, numpy >= 1.9 closes pandas-dev#15543, matplotlib >= 1.4.3 scipy >= 0.14.0 * CLN: replace %s syntax with .format in core.tools, algorithms.py, base.py (pandas-dev#17305) * BUG: Fix strange behaviour of Series.iloc on MultiIndex Series (pandas-dev#17148) (pandas-dev#17291) * DOC: Add module doc-string to tseries/api.py * MAINT: Clean up docs in pandas/errors/__init__.py * CLN: replace %s syntax with .format in missing.py, nanops.py, ops.py (pandas-dev#17322) Replaced %s syntax with .format in missing.py, nanops.py, ops.py. Additionally, made some of the existing positional .format code more explicit. * Make pd.Period immutable (pandas-dev#17239) * Bug: groupby multiindex levels equals rows (pandas-dev#16859) closes pandas-dev#16843 * BUG: Cannot use tz-aware origin in to_datetime (pandas-dev#16842) closes pandas-dev#16842 Author: step4me <prosikeffect@gmail.com> Closes pandas-dev#17244 from step4me/step4me-feature and squashes the following commits: 09d051d [step4me] BUG: Cannot use tz-aware origin in to_datetime (pandas-dev#16842) * Replace usage of total_seconds compat func with timedelta method (pandas-dev#17289) * CLN: replace %s syntax with .format in core/indexing.py (pandas-dev#17357) Progress toward issue pandas-dev#16130. Converted old string formatting to new string formatting in core/indexing.py. * DOC: Point to dev-docs in issue template (pandas-dev#17353) [ci skip] * CLN: remove total_seconds compat from json (pandas-dev#17341) * CLN: Move test_intersect_str_dates (pandas-dev#17366) Moves test_intersect_str_dates from tests/indexes/test_range.py to tests/indexes/test_base.py. * BUG: Respect dups in reindexing CategoricalIndex (pandas-dev#17355) When the indexer is identical to the elements. We should still return duplicates when the indexer contains duplicates. Closes pandas-devgh-17323. * Unify Index._dir_* with Series implementation (pandas-dev#17117) * BUG: make order of index from pd.concat deterministic (pandas-dev#17364) closes pandas-dev#17344 * Fix typo that causes several NaT methods to have incorrect docstrings (pandas-dev#17327) * CLN: replace %s syntax with .format in io/formats/format.py (pandas-dev#17358) Progress toward issue pandas-dev#16130. Converted old string formatting to new string formatting in io/formats/format.py. * PKG: Added pyproject.toml for PEP 518 (pandas-dev#16745) Declaring build-time requirements: https://www.python.org/dev/peps/pep-0518/ * DOC: Update Overview page in documentation (pandas-dev#17368) * Update Overview page in documentation * DOC Revise Overview page * DOC Make further revisions in Overview webpage * Update overview.rst Remove references to Panel * API: Have MultiIndex consturctors always return a MI (pandas-dev#17236) * API: Have MultiIndex constructors return MI This removes the special case for MultiIndex constructors returning an Index if all the levels are length-1. Now this will return a MultiIndex with a single level. This is a backwards incompatabile change, with no clear method for deprecation, so we're making a clean break. Closes pandas-dev#17178 * fixup! API: Have MultiIndex constructors return MI * Update for comments

guillemborrell mentioned this pull request May 5, 2017

rolling.quantile returns an interpolated result #16216

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guillemborrell changed the title ~~rolling.quantile now returns an interpolated result~~ BUG: rolling.quantile does not return an interpolated result May 5, 2017

jaimefrio reviewed May 5, 2017

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jreback requested changes May 7, 2017

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jreback added Bug Numeric Operations Arithmetic, Comparison, and Logical operations Reshaping Concat, Merge/Join, Stack/Unstack, Explode labels May 7, 2017

guillemborrell commented May 8, 2017

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jaimefrio approved these changes May 9, 2017

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guillemborrell commented May 10, 2017

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jreback reviewed May 10, 2017

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jreback approved these changes Jul 7, 2017

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guillemborrell and others added 4 commits July 7, 2017 15:27

BUG: rolling.quantile now returns an interpolated result (#9413)

fa971a2

Implemented changes suggested by reviewer @jaimefrio

ad8c034

quantile 1.0 and 0.0 are handled by the wrapper.

18da308

Move entry in Whatsnew to Groupby/Resample/Rolling

69b0a48

Guillem Borrell and others added 5 commits July 7, 2017 15:28

Added benchmarks for rolling windows

3acc6fd

Implemented changes suggested by reviewer @jaimefrio

b9dc329

quantile 1.0 and 0.0 are handled by the wrapper.

b94bda2

Move entry in Whatsnew to Groupby/Resample/Rolling

79e905f

Added benchmarks for rolling windows

fa4e036

jreback added this to the 0.21.0 milestone Jul 7, 2017

jreback requested changes Jul 7, 2017

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guillemborrell added 2 commits July 7, 2017 17:24

Fixed whatsnew syntax and comments on new tests.

b99e2be

Fixed trailing whitespace to make the linter happy

4080942

jreback approved these changes Jul 7, 2017

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jreback merged commit a43c157 into pandas-dev:master Jul 10, 2017

		- Bug in ``infer_freq`` causing indices with 2-day gaps during the working week to be wrongly inferred as business daily (:issue:`16624`)
		- Bug in ``.rolling.quantile()`` which incorrectly used different defaults than Series.quantile() and DataFrame.quantile()

BUG: rolling.quantile does not return an interpolated result #16247

BUG: rolling.quantile does not return an interpolated result #16247

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