Optionally disallow duplicate labels #28394

TomAugspurger · 2019-09-11T22:13:09Z

This adds a property to NDFrame to disallow duplicate labels. This fixes a vexing issue with using pandas for ETL pipelines, where accidentally introducing duplicate labels can lead to confusing downstream behavior (e.g. NDFrame.__getitem__ not reducing dimensionality).

When set (via the construction with allow_duplicate_labels=False or afterward via .allows_duplicate_labels=False), the presence of duplicate labels causes a DuplicateLabelError exception to be raised:

In [3]: df = pd.DataFrame({"A": [1, 2]}, index=['a', 'a'], allow_duplicate_labels=False)
---------------------------------------------------------------------------
DuplicateLabelError                       Traceback (most recent call last)
<ipython-input-3-1c8833763dfc> in <module>
----> 1 df = pd.DataFrame({"A": [1, 2]}, index=['a', 'a'], allow_duplicate_labels=False)

~/sandbox/pandas/pandas/core/frame.py in __init__(self, data, index, columns, dtype, copy, allow_duplicate_labels)
    493
    494         NDFrame.__init__(
--> 495             self, mgr, fastpath=True, allow_duplicate_labels=allow_duplicate_labels
    496         )
    497

~/sandbox/pandas/pandas/core/generic.py in __init__(self, data, axes, copy, dtype, allow_duplicate_labels, fastpath)
    202
    203         if not self.allows_duplicate_labels:
--> 204             self._maybe_check_duplicate_labels()
    205
    206     def _init_mgr(self, mgr, axes=None, dtype=None, copy=False):

~/sandbox/pandas/pandas/core/generic.py in _maybe_check_duplicate_labels(self, force)
    240         if force or not self.allows_duplicate_labels:
    241             for ax in self.axes:
--> 242                 ax._maybe_check_unique()
    243
    244     @property

~/sandbox/pandas/pandas/core/indexes/base.py in _maybe_check_unique(self)
    540             # TODO: position, value, not too large.
    541             msg = "Index has duplicates."
--> 542             raise DuplicateLabelError(msg)
    543
    544     # --------------------------------------------------------------------

DuplicateLabelError: Index has duplicates.

This property is preserved through operations (using _metadata and __finalize__).

In [4]: df = pd.DataFrame(index=['a', 'A'], allow_duplicate_labels=False)

In [5]: df.rename(str.upper)
---------------------------------------------------------------------------
DuplicateLabelError                       Traceback (most recent call last)
<ipython-input-5-17c8fb0b7c7f> in <module>
----> 1 df.rename(str.upper)
...

~/sandbox/pandas/pandas/core/indexes/base.py in _maybe_check_unique(self)
    540             # TODO: position, value, not too large.
    541             msg = "Index has duplicates."
--> 542             raise DuplicateLabelError(msg)
    543
    544     # --------------------------------------------------------------------

DuplicateLabelError: Index has duplicates.

API design questions

Do we want to be positive or negative?

pd.Series(..., allow_duplicate_labels=True/False)
pd.Series(..., disallow_duplicate_labels=False/True)
pd.Series(..., require_unique_labels=False/True)

In my proposal, the argument is different from the property. Do we like that? The rational is the argument is making a statement about what to do, while the property is making a statement about what is allowed.

In [7]: s = pd.Series(allow_duplicate_labels=False)

In [8]: s.allows_duplicate_labels
Out[8]: False

I'd like a method-chainable way of saying "duplicates aren't allowed." Some options

# two methods.
s.disallow_duplicate().allow_duplicate()

I dislike that in combination with .allows_duplicates, since we'd have a property and a method that only differ by an s. Perhaps something like

s.update_metdata(allows_duplicates=False)

But do people know that "allows_duplicates" is considered metadata?

TODO:

many, many more tests
Propagate metadata in more places (groupby, rolling, etc.)
Backwards compatibility in __finalize__ (we may be changing when we call it, and what we pass)

Apologies for using the PR for discussion, but we needed a way to compare this to #28334.

pandas/core/generic.py

TomAugspurger · 2019-09-12T14:49:58Z

I think this is ready for an initial review, to decide if this direction / behavior is OK. I'd recommend starting with the new docs section for the behavior, and NDFrame.__finalize__ for the implementation.

cc @jorisvandenbossche @jreback @jbrockmendel @jschendel @datapythonista @ others I'm sure.

datapythonista · 2019-09-12T15:04:42Z

This looks very useful, thanks for the work on this. I can't think of a better API, so happy with your proposal.

Just wondering if in the future we may want allow_duplicate_values=False by default, but that's surely something to leave for later and keep backward-compatibility here.

TomAugspurger · 2019-09-12T15:16:38Z

Just wondering if in the future we may want allow_duplicate_values=False by default

Yeah I think that's a possibility. But yes let's leave it for later :)

jschendel · 2019-09-12T18:59:15Z

doc/source/user_guide/duplicates.rst

+or column labels. This may be a bit confusing at first. If you're familiar with
+SQL, you know that row labels are similar to a primary key on a table, and you
+would never want duplicates in a SQL table. But one of pandas' roles is to clean
+mess, real-world data before it goes to some downstream system. And real-world


mess --> messy?

jschendel · 2019-09-12T22:53:11Z

I'm +1 on this.

A couple passing comments:

I found it a little bit confusing that the constructor parameter is allow_duplicate_labels but the attribute name is slightly different in allows_duplicate_labels. My preference here would be to make these the same.
Is there any utility in making this configurable at the axis level, i.e. allow a dataframe to have duplicate index labels but not have duplicate column labels?
- I don't think this is terribly important but anticipate that we'll get a user request for that feature, so probably best to bring this up now.

One thing I noticed is that this doesn't appear to validate when you directly assign a new index:

In [2]: s = pd.Series(list('abc'), allow_duplicate_labels=False)

In [3]: s.index = [0, 0, 0]

In [4]: s
Out[4]: 
0    a
0    b
0    c
dtype: object

In [5]: s.allows_duplicate_labels
Out[5]: False

jbrockmendel · 2019-09-12T23:18:59Z

Once a kwarg is in the Series constructor it can be difficult to get it out (see: fastpath). Could we put this in stealth mode for a while with something like:

ser = pd.Series(call_constructor_like_always)
ser._allows_duplicate_labels = False

Not a strong opinion, just thinking out loud.

WillAyd · 2019-09-13T01:02:36Z

Just out of curiosity why do you think adding this as a keyword argument to the Series / DataFrame constructor is the right approach? Would that subsequently guard against doing something like ser.index = list("aaa") after construction?

TomAugspurger · 2019-09-13T18:42:06Z

I found it a little bit confusing that the constructor parameter is allow_duplicate_labels but the attribute name is slightly different in allows_duplicate_labels. My preference here would be to make these the same.

I share this concern. Do others? After using it for a few days I'm getting used to it, but still need to stop and think.

Is there any utility in making this configurable at the axis level, i.e. allow a dataframe to have duplicate index labels but not have duplicate column labels?

Yes. My backwards-compatible plan here is to have the setter allow True/False/index/columns.

* True : allows duplicates everywhere
* False : allows duplicates nowhere
* index : allows duplicates in the index, but not in the columns
* columns : allows duplicates in the columns, but not in the index.

Code-wise, it's not much effort to support. It just makes the logic a bit more complicated, so I'm holding off for now.

Once a kwarg is in the Series constructor it can be difficult to get it out (see: fastpath). Could we put this in stealth mode for a while with something like:

Do we anticipate needing to remove this? Certainly, it can be marked as experimental if there's trepidation.

Just out of curiosity why do you think adding this as a keyword argument to the Series / DataFrame constructor is the right approach?

Initially, I was thinking it'd be a property on Index. I think that's more natural, since it's making a statement about the Index. But users interact more with Series / DataFrame, so I think it's more ergonomic to place it there.

After implementing things, putting it on NDFrame is nice because we have NDFrame.__finalize__ If it were on the index, things would be a be trickier.

jbrockmendel · 2019-09-13T21:00:45Z

Do we anticipate needing to remove this? Certainly, it can be marked as experimental if there's trepidation.

I don't anticipate needing to remove this, but I do anticipate other conceptually similar flags being implemented. In that scenario, I don't like the idea of all of these becoming kwargs in the Series constructor.

This aids in the implementation of pandas-dev#28394. Over there, I'm having issues with using `NDFrame.__finalize__` to copy attributes, in part because getattribute on NDFrame is so complicated. This simplifies this because we only need to look in NDFrame.attrs, which is just a plain dictionary. Aside from the addition of a public NDFrame.attrs dictionary, there aren't any user-facing API changes.

commit 67a3263 Author: Tom Augspurger <[email protected]> Date: Fri Oct 18 08:05:04 2019 -0500 fixup name commit e6183cd Author: Tom Augspurger <[email protected]> Date: Fri Oct 18 07:05:33 2019 -0500 fixup Index.name commit d1826bb Author: Tom Augspurger <[email protected]> Date: Thu Oct 17 13:45:30 2019 -0500 REF: Store metadata in attrs dict This aids in the implementation of pandas-dev#28394. Over there, I'm having issues with using `NDFrame.__finalize__` to copy attributes, in part because getattribute on NDFrame is so complicated. This simplifies this because we only need to look in NDFrame.attrs, which is just a plain dictionary. Aside from the addition of a public NDFrame.attrs dictionary, there aren't any user-facing API changes.

TomAugspurger · 2019-10-23T21:55:13Z

I'm seeing some strange mypy issues with these changes. Lots of

pandas/tests/test_strings.py:206: error: List item 0 has incompatible type "Type[Series]"; expected "Type[PandasObject]"
pandas/tests/test_strings.py:240: error: List item 0 has incompatible type "Type[Series]"; expected "Type[PandasObject]"
...

L206 is @pytest.mark.parametrize("box", [Series, Index]).

In fact, I'm seeing these mypy errors with just the following diff from master

diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index ef4e3e064d..7445951536 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -407,6 +407,7 @@ class DataFrame(NDFrame):
         columns: Optional[Axes] = None,
         dtype: Optional[Dtype] = None,
         copy: bool = False,
+        allow_duplicate_labels: bool = True,
     ):
         if data is None:
             data = {}
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index d59ce8db9b..64a38ca4eb 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -207,6 +207,7 @@ class NDFrame(PandasObject, SelectionMixin):
         dtype: Optional[Dtype] = None,
         attrs: Optional[Mapping[Optional[Hashable], Any]] = None,
         fastpath: bool = False,
+        allow_duplicate_labels: bool = True,
     ):
 
         if not fastpath:
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 3e9d3d5c04..8d6beb42c4 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -203,7 +203,7 @@ class Series(base.IndexOpsMixin, generic.NDFrame):
     # Constructors
 
     def __init__(
-        self, data=None, index=None, dtype=None, name=None, copy=False, fastpath=False
+        self, data=None, index=None, dtype=None, name=None, copy=False, fastpath=False, allow_duplicate_labels=True,
     ):
 
         # we are called internally, so short-circuit

Any ideas what's going wrong (perhaps @simonjayhawkins or @WillAyd have a guess)?

WillAyd · 2019-10-23T22:02:24Z

What version of mypy / pytest are you using? Seems strange for that to pop up if that is your only diff

Working around a strange typing issue. See pandas-dev#28394 (comment) for more, but the types on these were being inferred incorrectly by mypy with just the addition of the `allows_duplicate_labels` kwarg.

TomAugspurger · 2019-10-24T14:01:23Z

pytest 5.2.1
mypy 0.720

Indeed, it's quite strange. Opened #29205 to add explicit types to the tests that were failing.

simonjayhawkins · 2019-10-24T15:24:43Z

on master

reveal_type([Series, Index]) gives Revealed type is 'builtins.list[builtins.type*]'

with the changes in this PR..

Revealed type is 'builtins.list[def (data: Any =, Any =, Any =, name: Any =, Any =, Any =, **Any) -> pandas.core.base.PandasObject]'

simonjayhawkins · 2019-10-24T15:46:46Z

same inferred type with mypy 0.730 and 0.740

jreback · 2020-01-01T17:21:43Z

@TomAugspurger status of this

TomAugspurger · 2020-01-01T17:39:08Z

Still interested in working on it, but not happening for for 1.0.

…

On Wed, Jan 1, 2020 at 11:21 AM Jeff Reback ***@***.***> wrote: @TomAugspurger <https://github.com/TomAugspurger> status of this — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#28394?email_source=notifications&email_token=AAKAOIWMFJXLSIRR6U3C5D3Q3TGKRA5CNFSM4IVZNIOKYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEH5JALQ#issuecomment-570069038>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAKAOISNENLHU2JZMPFPUC3Q3TGKRANCNFSM4IVZNIOA> .

TomAugspurger · 2020-08-25T11:01:21Z

Just the windows s3 failures, which I think that #35856 is tracking.

TomAugspurger · 2020-08-26T20:52:55Z

CI is green now.

jreback

nice updates

a few inline questions

can u ensure that this can survive a round trip pickle (flags)
worth separating out index and columns flags for duplicates? eg i almost always care about column duplicates but may want to allow row dupes

doc/source/user_guide/duplicates.rst

pandas/core/flags.py

pandas/core/frame.py

jreback

a couple of inline comments

can u ensure this survives a round trip pickle (flags)

worth having separate flags for index and columns ? eg disallow column but allow for rows i would say is common

the reason to do this now is that it would be very hard to change later

jreback · 2020-08-26T22:06:01Z

i think my comments got duped as internet not great

TomAugspurger · 2020-08-27T11:56:44Z

worth separating out index and columns flags for duplicates? eg i almost always care about column duplicates but may want to allow row dupes

Possibly. The current system is future-compatible with that though, allows_duplicate_labels="index" / "columns"

TomAugspurger · 2020-08-27T12:06:37Z

Added the pickle test.

TomAugspurger · 2020-08-31T12:50:55Z

All green with the pickle test now.

I've also added tests that assert_eq correctly compares .flags. I think we would (by default) consider tm.assert_frame_equal(a, b) to be False when the flags don't match.

jreback

couple of minor comments and questions. looks good

doc/source/user_guide/duplicates.rst

doc/source/whatsnew/v1.2.0.rst

pandas/core/generic.py

pandas/core/indexes/base.py

jreback · 2020-08-31T23:57:26Z

pandas/core/indexes/base.py

@@ -483,6 +483,26 @@ def _simple_new(cls, values, name: Label = None):
    def _constructor(self):
        return type(self)

+    def _maybe_check_unique(self):
+        if not self.is_unique:
+            # TODO: position, value, not too large.


yeah maybe an arg to show the first 10 duplicates

It's truncated, following our usual repr's settings. I'll remove the todo

In [3]: s = pd.Series(1, index=[0] * 200).set_flags(allows_duplicate_labels=False) --------------------------------------------------------------------------- DuplicateLabelError Traceback (most recent call last) <ipython-input-3-ece63ed32110> in <module> ----> 1 s = pd.Series(1, index=[0] * 200).set_flags(allows_duplicate_labels=False) ~/sandbox/pandas/pandas/core/generic.py in set_flags(self, copy, allows_duplicate_labels) 349 df = self.copy(deep=copy) 350 if allows_duplicate_labels is not None: --> 351 df.flags["allows_duplicate_labels"] = allows_duplicate_labels 352 return df 353 ~/sandbox/pandas/pandas/core/flags.py in __setitem__(self, key, value) 103 if key not in self._keys: 104 raise ValueError(f"Unknown flag {key}. Must be one of {self._keys}") --> 105 setattr(self, key, value) 106 107 def __repr__(self): ~/sandbox/pandas/pandas/core/flags.py in allows_duplicate_labels(self, value) 90 if not value: 91 for ax in obj.axes: ---> 92 ax._maybe_check_unique() 93 94 self._allows_duplicate_labels = value ~/sandbox/pandas/pandas/core/indexes/base.py in _maybe_check_unique(self) 491 msg += "\n{}".format(duplicates) 492 --> 493 raise DuplicateLabelError(msg) 494 495 def _format_duplicate_message(self): DuplicateLabelError: Index has duplicates. positions label 0 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...

In [10]: s = pd.Series(1, index=np.arange(100).repeat(10)).set_flags(allows_duplicate_labels=False) --------------------------------------------------------------------------- DuplicateLabelError Traceback (most recent call last) <ipython-input-10-452fca37a730> in <module> ----> 1 s = pd.Series(1, index=np.arange(100).repeat(10)).set_flags(allows_duplicate_labels=False) ~/sandbox/pandas/pandas/core/generic.py in set_flags(self, copy, allows_duplicate_labels) 349 df = self.copy(deep=copy) 350 if allows_duplicate_labels is not None: --> 351 df.flags["allows_duplicate_labels"] = allows_duplicate_labels 352 return df 353 ~/sandbox/pandas/pandas/core/flags.py in __setitem__(self, key, value) 103 if key not in self._keys: 104 raise ValueError(f"Unknown flag {key}. Must be one of {self._keys}") --> 105 setattr(self, key, value) 106 107 def __repr__(self): ~/sandbox/pandas/pandas/core/flags.py in allows_duplicate_labels(self, value) 90 if not value: 91 for ax in obj.axes: ---> 92 ax._maybe_check_unique() 93 94 self._allows_duplicate_labels = value ~/sandbox/pandas/pandas/core/indexes/base.py in _maybe_check_unique(self) 491 msg += "\n{}".format(duplicates) 492 --> 493 raise DuplicateLabelError(msg) 494 495 def _format_duplicate_message(self): DuplicateLabelError: Index has duplicates. positions label 0 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] 1 [10, 11, 12, 13, 14, 15, 16, 17, 18, 19] 2 [20, 21, 22, 23, 24, 25, 26, 27, 28, 29] 3 [30, 31, 32, 33, 34, 35, 36, 37, 38, 39] 4 [40, 41, 42, 43, 44, 45, 46, 47, 48, 49] ... ... 95 [950, 951, 952, 953, 954, 955, 956, 957, 958, ... 96 [960, 961, 962, 963, 964, 965, 966, 967, 968, ... 97 [970, 971, 972, 973, 974, 975, 976, 977, 978, ... 98 [980, 981, 982, 983, 984, 985, 986, 987, 988, ... 99 [990, 991, 992, 993, 994, 995, 996, 997, 998, ... [100 rows x 1 columns]

jreback

lgtm. thanks @TomAugspurger

TomAugspurger · 2020-09-03T11:26:22Z

Thanks!

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REF/ENH: Refactor NDFrame finalization #28334

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TomAugspurger added metadata _metadata, .attrs API Design labels Sep 13, 2019

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REF: Store metadata in an attrs dict #29062

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TYPING: Added types for some tests #29205

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DataFrame.groupby doesn't preserve _metadata #29442

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Optionally disallow duplicate labels (pandas-dev#28394)

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