ENH: pd.Series.shift and .diff to accept a collection of numbers #44660
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skwirskj
commented
Nov 28, 2021
•
skwirskj
commented
- closes ENH: pd.Series.shift and .diff to accept a collection of numbers #44424
- tests added / passed
- Ensure all linting tests pass, see here for how to run them
- whatsnew entry
…e shift functions to allow iterables to be passed as the period
…ake in a list for periods and then return a concatenated DataFrame of each consecutive shift in the periods list
…llection Merging the master branch with my changes for Enhancement at issue 44424
Created two new tests to test shifting data in Series and DataFrames with an iterable as the period parameter.
…llection Merging after updating tests and resetting the generic.py file
Reverted some changes that were made when originally finding a solution and then reset it to the latest version on the upstream master branch.
jreback
requested changes
Nov 28, 2021
phofl
reviewed
Nov 28, 2021
phofl
reviewed
Nov 28, 2021
Updated how we are creating the new DataFrame after shifting to improve performance. Also reverted core/generic.py to master
Attempting to fix whatsnew rst file
rhshadrach
reviewed
Dec 4, 2021
jreback
requested changes
Dec 9, 2021
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| Usage within the :class:`DataFrame` class: | ||
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| .. ipython:: python |
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this is fine, but the main source of information is the doc-strings which need updating with examples & prose.
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| The :meth:`DataFrame.shift` and :meth:`Series.shift` functions can take in an iterable, such as a list, for the period parameter. When an iterable is passed | ||
| to either function it returns a :class:`DataFrame` object with all of the shifted rows or columns concatenated with one another. | ||
| The function applies a shift designated by each element in the iterable. The resulting :class:`DataFrame` object's columns will retain the |
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you don't need this sentence to the end. you can say that the suffix parameter controls the names but don't have to fully explain here. that's the point of the doc-string.
| ) -> DataFrame: | ||
| axis = self._get_axis_number(axis) | ||
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| # GH#44424 Handle the case of multiple shifts |
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if axis==1 this should fail
| for i in periods: | ||
| if not isinstance(i, int): | ||
| raise TypeError( | ||
| f"Value {i} in periods is not an integer, expected an integer" |
| # GH#44424 Handle the case of multiple shifts | ||
| if is_list_like(periods): | ||
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| new_df = DataFrame() |
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| from pandas.core.reshape.concat import concat | ||
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| new_df_list = [] |
| ) -> Series | DataFrame: | ||
| # Handle the case of multiple shifts | ||
| if is_list_like(periods): | ||
| if len(periods) == 0: |
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is this tested? this should be an error i think
| if len(periods) == 0: | ||
| return self | ||
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| df = self.to_frame() |
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why are you doing this? shouldn't you just be concatting the result series?
| @@ -429,3 +429,23 @@ def test_shift_axis1_categorical_columns(self): | |||
| columns=ci, | |||
| ) | |||
| tm.assert_frame_equal(result, expected) | |||
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| def test_shift_with_iterable(self): | |||
| # GH#44424 | |||
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what about error conditions
| @@ -376,3 +377,15 @@ def test_shift_non_writable_array(self, input_data, output_data): | |||
| expected = Series(output_data, dtype="float64") | |||
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| tm.assert_series_equal(result, expected) | |||
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| def test_shift_with_iterable(self): | |||
| # GH#44424 | |||
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This pull request is stale because it has been open for thirty days with no activity. Please update and respond to this comment if you're still interested in working on this. |
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closing as stale if you want continue, pls ping |
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sure |
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