ENH: allow get_dummies to accept dtype argument #18330

Scorpil · 2017-11-16T21:29:01Z

closes ENH: allow get_dummies to accept dtype argument #18330 (there's no issue for this one)
tests added / passed
passes git diff upstream/master -u -- "*.py" | flake8 --diff
whatsnew entry

Update in version 0.19.0 made get_dummies return uint8 values instead of floats (#8725). While I agree with the argument that get_dummies should output integers by default (to save some memory), in many cases it would be beneficial for user to choose other dtype.

In my case there was serious performance degradation between versions 0.18 and 0.19. After investigation, reason behind it turned out to be the change to get_dummies output type. DataFrame with dummy values was used as an argument to np.dot in an optimization function (second argument was matrix of floats). Since there were lots of iterations involved, and on each iteration np.dot was converting all uint8 values to float64, conversion overhead took unreasonably long time. It is possible to work around this issue by converting dummy columns "manually" afterwards, but it adds unnecessary complexity to the code and is clearly less convenient than calling get_dummies with dtype=float.

Apart from performance considerations, I can imagine dtype=bool to be a common use case.

get_dummies(data, dtype=None) is allowed and will return uint8 values to match the DataFrame interface (where None allows inferring datatype, which is default behavior).

I've extended the test suite to run all the get_dummies tests (except for those that don't deal with internal dtypes, like test_just_na) twice, once with uint8 and once with float64.

codecov · 2017-11-16T22:41:16Z

Codecov Report

Merging #18330 into master will decrease coverage by 0.01%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master   #18330      +/-   ##
==========================================
- Coverage   91.35%   91.33%   -0.02%     
==========================================
  Files         163      163              
  Lines       49714    49719       +5     
==========================================
- Hits        45415    45410       -5     
- Misses       4299     4309      +10

Flag	Coverage Δ
#multiple	`89.13% <100%> (-0.01%)`	⬇️
#single	`39.63% <0%> (-0.07%)`	⬇️

Impacted Files	Coverage Δ
pandas/core/generic.py	`95.73% <ø> (ø)`	⬆️
pandas/core/reshape/reshape.py	`100% <100%> (ø)`	⬆️
pandas/io/gbq.py	`25% <0%> (-58.34%)`	⬇️
pandas/core/frame.py	`97.8% <0%> (-0.1%)`	⬇️
pandas/core/indexes/datetimes.py	`95.39% <0%> (-0.1%)`	⬇️

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jreback · 2017-11-17T00:17:44Z

pandas/core/reshape/reshape.py

@@ -725,6 +725,8 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
    drop_first : bool, default False
        Whether to get k-1 dummies out of k categorical levels by removing the
        first level.
+    dtype : dtype, default np.uint8


add a versionadded tag

jreback · 2017-11-17T00:18:38Z

pandas/tests/reshape/test_reshape.py

@@ -217,34 +217,36 @@ def test_multiindex(self):


 class TestGetDummies(object):


instead of doing this define a fixture that returns the various dtypes that you are testing

jreback · 2017-11-17T00:19:33Z

doc/source/whatsnew/v0.22.0.txt

@@ -140,7 +140,7 @@ Sparse
 Reshaping
 ^^^^^^^^^

-
+- :func:`get_dummies` now supports ``dtype`` argument


add a little more expl, add the PR number as the issue number. Move to Other Enhancements section.

Scorpil · 2017-11-18T20:45:26Z

All done. Also updated sparse tests to use fixtures as well. And added one test to verify effective dtype is uint8 when dtype argument is None.

jreback

looks good generally. thanks for parametrizing the tests!

jreback · 2017-11-19T15:43:58Z

doc/source/whatsnew/v0.22.0.txt

@@ -24,7 +24,17 @@ Other Enhancements

 - Better support for :func:`Dataframe.style.to_excel` output with the ``xlsxwriter`` engine. (:issue:`16149`)
 - :func:`pandas.tseries.frequencies.to_offset` now accepts leading '+' signs e.g. '+1h'. (:issue:`18171`)
-


make a separate sub-section for this

jreback · 2017-11-19T15:44:10Z

doc/source/whatsnew/v0.22.0.txt

@@ -24,7 +24,17 @@ Other Enhancements

 - Better support for :func:`Dataframe.style.to_excel` output with the ``xlsxwriter`` engine. (:issue:`16149`)
 - :func:`pandas.tseries.frequencies.to_offset` now accepts leading '+' signs e.g. '+1h'. (:issue:`18171`)
-
+- :func:`pandas.get_dummies` now supports ``dtype`` argument, which forces specific dtype for new columns. (:issue:`18330`)


say default is the same (uint8)

jreback · 2017-11-19T15:44:26Z

doc/source/whatsnew/v0.22.0.txt

-
+- :func:`pandas.get_dummies` now supports ``dtype`` argument, which forces specific dtype for new columns. (:issue:`18330`)
+
+.. code-block:: ipython


use an ipython block, show the original as well (first)

jreback · 2017-11-19T15:45:37Z

pandas/tests/reshape/test_reshape.py

-        self.df = DataFrame({'A': ['a', 'b', 'a'],
-                             'B': ['b', 'b', 'c'],
-                             'C': [1, 2, 3]})
+    @pytest.fixture(params=['uint8', 'float64'])


cycle thru more dtypes here that are valid (doesn't have to be all, but include int64, bool, IOW valid for both sparse/dense)

add None as well

we should prob raise on object dtype I think.

jreback · 2017-11-19T15:46:11Z

pandas/tests/reshape/test_reshape.py

+        expected = DataFrame({'a': [1, 0, 0],
+                              'b': [0, 1, 0],
+                              'c': [0, 0, 1]}, dtype=dtype)
+        result = get_dummies(s_list, **kwargs)


I wouldn't construct the kwargs, actually just pass directly

jreback · 2017-11-19T15:47:16Z

pandas/tests/reshape/test_reshape.py

        assert_frame_equal(res, exp)

        # Sparse dataframes do not allow nan labelled columns, see #GH8822
-        res_na = get_dummies(s, dummy_na=True, sparse=self.sparse)
+        res_na = get_dummies(s, dummy_na=True, **kwargs)


see my comment above, don't use kwargs generally for passing args to test functions, rather pass directly

jreback · 2017-11-19T15:49:10Z

@TomAugspurger

pep8speaks · 2017-11-19T20:02:18Z

Hello @Scorpil! Thanks for updating the PR.

Cheers ! There are no PEP8 issues in this Pull Request. 🍻

Comment last updated on November 22, 2017 at 13:15 Hours UTC

jreback · 2017-11-19T20:07:59Z

doc/source/whatsnew/v0.22.0.txt

@@ -24,7 +24,27 @@ Other Enhancements

 - Better support for :func:`Dataframe.style.to_excel` output with the ``xlsxwriter`` engine. (:issue:`16149`)
 - :func:`pandas.tseries.frequencies.to_offset` now accepts leading '+' signs e.g. '+1h'. (:issue:`18171`)
-
+
+``get_dummies`` now supports ``dtype`` argument


add a ref here as well.

jreback · 2017-11-19T20:09:57Z

doc/source/whatsnew/v0.22.0.txt

+``get_dummies`` now supports ``dtype`` argument
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+:func:`get_dummies` function now accepts ``dtype`` argument, which forces specific dtype for new columns. When ``dtype`` is not specified or equals to ``None``, new columns will have dtype ``uint8`` (as before), so this change is backwards compatible. (:issue:`18330`)


The :func:`get_dummies` function now accepts adtypeargument, which forces a specific dtype for the new columns. The default isuint8ifdtypeis not specified orNone``.

jreback · 2017-11-19T20:10:32Z

pandas/core/reshape/reshape.py

+    if dtype is None:
+        dtype = np.uint8
+
+    if np.dtype(dtype) is np.dtype('O'):


use is_object_dtype

jreback · 2017-11-19T20:10:51Z

pandas/core/reshape/reshape.py

+
+    if np.dtype(dtype) is np.dtype('O'):
+        raise TypeError("'object' is not a valid type for get_dummies")
+


this could be a ValueError; also so dtype=object is not a valid dtype for get_dummies

jreback · 2017-11-19T20:11:39Z

pandas/core/reshape/reshape.py

    return result


 def _get_dummies_1d(data, prefix, prefix_sep='_', dummy_na=False,
-                    sparse=False, drop_first=False):
+                    sparse=False, drop_first=False, dtype=np.uint8):


should this be passthru?

Right, missed this one. Idea was to treat this one as internal and allow "wrapper" to set dtype, but passthru has it's advantages and I don't mind ether way, so I'll move dtype-related conversions to this method.

TomAugspurger

Thanks.

I'll finish taking a look later but my only real concern is how many times you parametrize by the dtype. It's great to do that for some tests like test_basic_dtype and a few others, but I'm not sure about all the prefix / sep tests. Do you have specific concerns that you're trying to test there?

TomAugspurger · 2017-11-19T20:37:00Z

doc/source/whatsnew/v0.22.0.txt

+``get_dummies`` now supports ``dtype`` argument
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+:func:`get_dummies` function now accepts ``dtype`` argument, which forces specific dtype for new columns. When ``dtype`` is not specified or equals to ``None``, new columns will have dtype ``uint8`` (as before), so this change is backwards compatible. (:issue:`18330`)


Can remove function after get_dummies.

now accepts a dtype argument

replace forces with specifies a

Replace the second sentence with

When ``dtype`` is not specified, the dtype will be ``uint8`` as before.

TomAugspurger · 2017-11-19T20:41:07Z

doc/source/whatsnew/v0.22.0.txt

+.. ipython:: python
+
+   df = pd.DataFrame({'a': [1, 2], 'b': [3, 4], 'c': [5, 6]})
+   pd.get_dummies(df, columns=['c'])


I think you can remove the "Previous behavior" section since this is backwards compatible.

I'd just do

pd.get_dummies(df, columns=['c']).dtypes pd.get_dummies(df, columns=['c'], dtype=bool).dtypes

TomAugspurger · 2017-11-19T20:43:28Z

pandas/core/reshape/reshape.py

@@ -697,7 +697,7 @@ def _convert_level_number(level_num, columns):


 def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
-                columns=None, sparse=False, drop_first=False):
+                columns=None, sparse=False, drop_first=False, dtype=None):


Any reason not to use 'uint8' or np.uint8 here?

I've tried to mirror API of DataFrame, Series, Panel etc. where passing None explicitly is allowed and means "dtype will be inferred".

@jreback @TomAugspurger So this is the last question to answer. Do you accept my argument about None or should I change it to np.uint8?

this is ok here, it follows a similar style elsewhere

TomAugspurger · 2017-11-19T20:44:01Z

pandas/core/reshape/reshape.py

@@ -728,6 +728,11 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,

        .. versionadded:: 0.18.0

+    dtype : dtype, default np.uint8


Can we also accept arguments to np.dtype like the string 'i8', and handle those appropriately?

he is using np.dtype()?

Yes, that should work already, I'll add it to the tests.

TomAugspurger · 2017-11-19T20:45:55Z

pandas/tests/reshape/test_reshape.py

+        # e.g. TestGetDummies::test_basic[uint8-sparse] instead of [uint8-True]
+        return request.param == 'sparse'
+
+    def effective_dtype(self, dtype):


If we make the default np.uint8 you can remove this.

TomAugspurger · 2017-11-19T20:48:28Z

pandas/tests/reshape/test_reshape.py

+                          'C': [1, 2, 3]})
+
+    @pytest.fixture(params=['uint8', 'int64', np.float64, bool, None])
+    def dtype(self, request):


If we use this fixture in many places it's going to add a ton of tests.

these are all quick, so this is ok

Initially I only had 'uint8' and 'float64', but @jreback reasonably suggested to add some more. What would be a good balance here? If I'll remove usage of this fixture from all the unrelated tests like prefix / separator tests, and move None to separate stand-alone test, would ['uint8', 'i8', np.float64, bool] be OK? Still x4 number of tests, but each item uses a different way to specify dtype, so i think it's meaningful set of fixtures.

i think toms point is to not apply this fixture to every test (just relevant ones)

TomAugspurger · 2017-11-19T20:51:09Z

pandas/tests/reshape/test_reshape.py

-    def test_dataframe_dummies_all_obj(self):
-        df = self.df[['A', 'B']]
-        result = get_dummies(df, sparse=self.sparse)
+    def test_dataframe_dummies_all_obj(self, df, sparse, dtype):


What's the benefit of parametrizing by dtype here?

TomAugspurger · 2017-11-19T20:52:12Z

pandas/tests/reshape/test_reshape.py

        assert_frame_equal(result, expected)

-    def test_dataframe_dummies_prefix_str(self):
+    def test_dataframe_dummies_prefix_str(self, df, sparse, dtype):


Same question. Is there any relationship between the prefix and dtype? The seem orthogonal.

TomAugspurger · 2017-11-19T20:52:45Z

pandas/tests/reshape/test_reshape.py

        assert_frame_equal(result, expected)

-    def test_dataframe_dummies_subset(self):
-        df = self.df
+    def test_dataframe_dummies_subset(self, df, sparse, dtype):


Same question: Any interaction between subset and dtype?

TomAugspurger · 2017-11-19T20:54:27Z

pandas/tests/reshape/test_reshape.py

-    def test_dataframe_dummies_prefix_sep(self):
-        df = self.df
-        result = get_dummies(df, prefix_sep='..', sparse=self.sparse)
+    def test_dataframe_dummies_prefix_sep(self, df, sparse, dtype):


Same question :)

jreback · 2017-11-20T11:26:31Z

doc/source/whatsnew/v0.22.0.txt

@@ -27,6 +27,17 @@ Other Enhancements
 - :class:`pandas.io.formats.style.Styler` now has method ``hide_index()`` to determine whether the index will be rendered in ouptut (:issue:`14194`)
 - :class:`pandas.io.formats.style.Styler` now has method ``hide_columns()`` to determine whether columns will be hidden in output (:issue:`14194`)



can you add a ref here

I'm sorry, not used to work with sphinx. Do you mean something like this here:

- :func:`get_dummies` now supports ``dtype`` argument, see :ref:`here <whatsnew_0220.enhancements.get_dummies_dtype>` for more (:issue: `18330`)

and then this before the actual description block:

.. _whatsnew_0220.enhancements.get_dummies_dtype

?

jreback · 2017-11-20T11:26:59Z

pandas/core/reshape/reshape.py

@@ -697,7 +697,7 @@ def _convert_level_number(level_num, columns):


 def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
-                columns=None, sparse=False, drop_first=False):
+                columns=None, sparse=False, drop_first=False, dtype=None):


this is ok here, it follows a similar style elsewhere

jreback · 2017-11-20T11:27:26Z

pandas/core/reshape/reshape.py

    See Also
    --------
    Series.str.get_dummies
    """
    from pandas.core.reshape.concat import concat
    from itertools import cycle

+    if dtype is None:
+        dtype = np.uint8
+


need a dtype = np.dtype(dtype)

jreback · 2017-11-20T11:27:36Z

pandas/core/reshape/reshape.py

    return result


 def _get_dummies_1d(data, prefix, prefix_sep='_', dummy_na=False,
-                    sparse=False, drop_first=False):
+                    sparse=False, drop_first=False, dtype=np.uint8):


TomAugspurger

Gave another quick glance, and things look good here.

TomAugspurger · 2017-11-20T22:43:58Z

pandas/tests/reshape/test_reshape.py

        # not that you should do this...
-        df = self.df
-        result = get_dummies(df, prefix='bad', sparse=self.sparse)
+        df[['C']] = df[['C']].astype(np.uint8)


Why the change here?

This test is a bit weird... Having 2 columns with identical names caused ValueError when I tried expected['C'] = expected['C']. Now, when you mentioned it, I see in diff that expected = expected.astype({"C": np.int64}) should work, I'll put it back.

TomAugspurger · 2017-11-20T22:46:41Z

pandas/tests/reshape/test_reshape.py

        df.loc[3, :] = [np.nan, np.nan, np.nan]
-        result = get_dummies(df, dummy_na=True, sparse=self.sparse)
+        result = get_dummies(df, dummy_na=True,


Did you add the sorting because the output changed, or to make the test easier to write?

I slightly prefer the explicit ordering rather than sorting, though that'll be covered elsewhere so changing it isn't a huge deal.

Just a bit easier to write.

jreback

lgtm. small doc changes. have a look in reshaping.rst if any doc updates are needed.

jreback · 2017-11-22T02:18:15Z

doc/source/whatsnew/v0.22.0.txt

@@ -28,6 +28,20 @@ Other Enhancements
 - :class:`pandas.io.formats.style.Styler` now has method ``hide_index()`` to determine whether the index will be rendered in ouptut (:issue:`14194`)
 - :class:`pandas.io.formats.style.Styler` now has method ``hide_columns()`` to determine whether columns will be hidden in output (:issue:`14194`)
 - Improved wording of ``ValueError`` raised in :func:`to_datetime` when ``unit=`` is passed with a non-convertible value (:issue:`14350`)
+- :func:`get_dummies` now supports ``dtype`` argument, see :ref:`here <whatsnew_0220.enhancements.get_dummies_dtype>` for more (:issue:`18330`)


you can remove this line, its already covered in the sub-section. move the sub-section before other enhancements

jreback · 2017-11-22T02:19:17Z

pandas/tests/reshape/test_reshape.py

+            return np.uint8
+        return dtype
+
+    def test_throws_on_dtype_object(self, df):


throws -> raises

jreback · 2017-11-22T11:14:57Z

doc/source/reshaping.rst

+
+    pd.get_dummies(df, dtype=bool).dtypes
+
+.. versionadded:: 0.22.0


ca you move to before the example

jreback · 2017-11-22T11:15:36Z

doc/source/whatsnew/v0.22.0.txt

+``get_dummies`` now supports ``dtype`` argument
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The :func:`get_dummies` now accepts a ``dtype`` argument, which specifies a specific dtype for the new columns. When ``dtype`` is not specified or ``None``, the dtype will be ``uint8`` as before. (:issue:`18330`)


just say the default remains uint8

Done. Also removed useless 'specific' in "specifies a ~~specific~~ dtype".

Scorpil · 2017-11-22T11:16:16Z

doc/source/reshaping.rst

@@ -240,7 +240,7 @@ values will be set to ``NaN``.
   df3
   df3.unstack()

-.. versionadded: 0.18.0
+.. versionadded:: 0.18.0


This was a typo, right? There are couple more places where second double column is missing:

pandas/core/frame.py 4516: .. versionadded: 0.18.0 4679: .. versionadded: 0.16.1 pandas/core/generic.py 968: .. versionadded: 0.21.0 pandas/core/series.py 1629: .. versionadded: 0.19.0 2216: .. versionadded: 0.18.0 pandas/core/tools/datetimes.py 117: .. versionadded: 0.18.1 143: .. versionadded: 0.16.1 181: .. versionadded: 0.20.0 187: .. versionadded: 0.22.0 pandas/tseries/offsets.py 778: .. versionadded: 0.16.1 882: .. versionadded: 0.18.1

hmm yes looks that way. would be great if you can update those! (if you really want to could also add a lint rule to search for these and fail the build if they are found) (also in doc dir too).

Separate PR or this will do?

separate PR prob better. (the one you changed already is fine). I think we DO want to add some more generic checks for these formatting tags, I guess sphinx doesn't complain

Yeah, it's just comments for sphinx. I'll create an issue then, and see what I can do when I have time to look into it. Or somebody will pick it up before that, which is also fine :)

jreback · 2017-11-22T11:16:23Z

pandas/core/reshape/reshape.py

    # Series avoids inconsistent NaN handling
    codes, levels = _factorize_from_iterable(Series(data))

+    if dtype is None:
+        dtype = np.uint8
+    else:


if dtype is None dtype = np.uint8 dtype = np.dtype(dtype)

a bit more idiomatic

jreback

small comments. ping on green.

Use pytest fixtures. Add test for dtype=None.

Scorpil · 2017-11-22T19:31:34Z

@jreback it's green.

jreback · 2017-11-22T23:03:29Z

thanks @Scorpil nice patch! keem em coming!

jreback requested changes Nov 17, 2017

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jreback added Dtype Conversions Unexpected or buggy dtype conversions Reshaping Concat, Merge/Join, Stack/Unstack, Explode labels Nov 17, 2017

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Scorpil force-pushed the get_dummies_dtype branch from 3d504fb to d93ee28 Compare November 19, 2017 20:02

Scorpil force-pushed the get_dummies_dtype branch from 0850ac7 to cb3156a Compare November 19, 2017 20:11

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TomAugspurger reviewed Nov 19, 2017

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Scorpil force-pushed the get_dummies_dtype branch from afbf368 to 6d447c3 Compare November 20, 2017 21:14

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Scorpil force-pushed the get_dummies_dtype branch 3 times, most recently from 8ab9859 to a1de373 Compare November 22, 2017 11:10

jreback reviewed Nov 22, 2017

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doc/source/reshaping.rst

pd.get_dummies(df, dtype=bool).dtypes

.. versionadded:: 0.22.0

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ca you move to before the example

jreback reviewed Nov 22, 2017

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Scorpil commented Nov 22, 2017

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jreback added this to the 0.22.0 milestone Nov 22, 2017

Scorpil added 5 commits November 22, 2017 12:22

TST: get_dummies dtype tests

a333fa9

ENH: add dtype argument to get_dummies

f84f83e

CLN: clean up lint errors

2737069

DOC: update whatsnew

c412dae

DOC: improve get_dummies dtype documentation

b869afe

Scorpil added 18 commits November 22, 2017 12:22

TST: change get_dummies test setup

7038b31

Use pytest fixtures. Add test for dtype=None.

DOC: more info for dtype argument of get_dummies in whatsnew

c412be0

ENH: raise TypeError for object dtype on get_dummies

769b3b6

TST: better tests for get_dummies dtype

20556f2

CLN: cleanup reshape test style

b3ec885

DOC: fix wording in whatsnew for get_dummies dtype argument

9e5d0bb

CLN: Raise ValueError on invalid dtype

b8ab365

TST: remove fixtures where not needed

9db17f2

TST: remove dtype fixture from subset test

ef7a473

TST: fix bug in get_dummy tests under python3

67d346d

TST: Remove dtype fixture where not needed

367e753

CLN: move dtype logic to internal function in get_dummies

4e47860

DOC: add ref to get_dummies entry in whatsnew

bf8327c

DOC: remove extra space in whatsnew

f3abd2b

TST: change dtype on expected output instead of input

649d303

DOC: update whatsnew, change test name

a7a60b7

DOC: add get_dummies dtype argument description to reshaping.rst

bc192fd

DOC: update whatsnew style, minore codestyle change

d19d81f

Scorpil force-pushed the get_dummies_dtype branch 2 times, most recently from fecb047 to d19d81f Compare November 22, 2017 13:12

DOC: fix typo and trigger tests

158a317

jreback approved these changes Nov 22, 2017

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jreback merged commit fedc503 into pandas-dev:master Nov 22, 2017

		@@ -217,34 +217,36 @@ def test_multiindex(self):


		class TestGetDummies(object):


		if np.dtype(dtype) is np.dtype('O'):
		raise TypeError("'object' is not a valid type for get_dummies")

		@@ -728,6 +728,11 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,

		.. versionadded:: 0.18.0

		dtype : dtype, default np.uint8

		@@ -27,6 +27,17 @@ Other Enhancements
		- :class:`pandas.io.formats.style.Styler` now has method ``hide_index()`` to determine whether the index will be rendered in ouptut (:issue:`14194`)
		- :class:`pandas.io.formats.style.Styler` now has method ``hide_columns()`` to determine whether columns will be hidden in output (:issue:`14194`)


		pd.get_dummies(df, dtype=bool).dtypes

		.. versionadded:: 0.22.0

ENH: allow get_dummies to accept dtype argument #18330

ENH: allow get_dummies to accept dtype argument #18330

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Scorpil commented Nov 16, 2017 • edited Loading

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Comment last updated on November 22, 2017 at 13:15 Hours UTC

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Scorpil commented Nov 22, 2017

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Scorpil commented Nov 16, 2017 •

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