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DOC, CI: Correct wide_to_long docstring and add reshape/melt to CI #26273

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May 3, 2019
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DOC, CI: Correct wide_to_long docstring and add reshape/melt to CI #26273

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3861066
DOC: Correct wide_to_long docstring
vandenn May 3, 2019
a1f8a63
CI: Add reshape/melt.py to CI checks
vandenn May 3, 2019
61b2793
DOC: Fix outputs in wide_to_long docstring to reflect actual results
vandenn May 3, 2019
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1 change: 1 addition & 0 deletions ci/code_checks.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -245,6 +245,7 @@ if [[ -z "$CHECK" || "$CHECK" == "doctests" ]]; then
pandas/core/reshape/pivot.py \
pandas/core/reshape/reshape.py \
pandas/core/reshape/tile.py \
pandas/core/reshape/melt.py \
-k"-crosstab -pivot_table -cut"
RET=$(($RET + $?)) ; echo $MSG "DONE"

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70 changes: 33 additions & 37 deletions pandas/core/reshape/melt.py
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Expand Up @@ -270,15 +270,15 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix=r'\d+'):
... 'ht2': [3.4, 3.8, 2.9, 3.2, 2.8, 2.4, 3.3, 3.4, 2.9]
... })
>>> df
birth famid ht1 ht2
famid birth ht1 ht2
0 1 1 2.8 3.4
1 2 1 2.9 3.8
2 3 1 2.2 2.9
3 1 2 2.0 3.2
1 1 2 2.9 3.8
2 1 3 2.2 2.9
3 2 1 2.0 3.2
4 2 2 1.8 2.8
5 3 2 1.9 2.4
6 1 3 2.2 3.3
7 2 3 2.3 3.4
5 2 3 1.9 2.4
6 3 1 2.2 3.3
7 3 2 2.3 3.4
8 3 3 2.1 2.9
>>> l = pd.wide_to_long(df, stubnames='ht', i=['famid', 'birth'], j='age')
>>> l
Expand Down Expand Up @@ -323,33 +323,29 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix=r'\d+'):
Less wieldy column names are also handled

>>> np.random.seed(0)
>>> df = pd.DataFrame({'A(quarterly)-2010': np.random.rand(3),
... 'A(quarterly)-2011': np.random.rand(3),
... 'B(quarterly)-2010': np.random.rand(3),
... 'B(quarterly)-2011': np.random.rand(3),
>>> df = pd.DataFrame({'A(weekly)-2010': np.random.rand(3),
... 'A(weekly)-2011': np.random.rand(3),
... 'B(weekly)-2010': np.random.rand(3),
... 'B(weekly)-2011': np.random.rand(3),
... 'X' : np.random.randint(3, size=3)})
>>> df['id'] = df.index
>>> df # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
A(quarterly)-2010 A(quarterly)-2011 B(quarterly)-2010 ...
0 0.548814 0.544883 0.437587 ...
1 0.715189 0.423655 0.891773 ...
2 0.602763 0.645894 0.963663 ...
X id
0 0 0
1 1 1
2 1 2

>>> pd.wide_to_long(df, ['A(quarterly)', 'B(quarterly)'], i='id',
A(weekly)-2010 A(weekly)-2011 B(weekly)-2010 B(weekly)-2011 X id
0 0.548814 0.544883 0.437587 0.383442 0 0
1 0.715189 0.423655 0.891773 0.791725 1 1
2 0.602763 0.645894 0.963663 0.528895 1 2

>>> pd.wide_to_long(df, ['A(weekly)', 'B(weekly)'], i='id',
... j='year', sep='-')
... # doctest: +NORMALIZE_WHITESPACE
X A(quarterly) B(quarterly)
X A(weekly) B(weekly)
id year
0 2010 0 0.548814 0.437587
1 2010 1 0.715189 0.891773
2 2010 1 0.602763 0.963663
0 2011 0 0.544883 0.383442
1 2011 1 0.423655 0.791725
2 2011 1 0.645894 0.528895
0 2010 0 0.548814 0.437587
1 2010 1 0.715189 0.891773
2 2010 1 0.602763 0.963663
0 2011 0 0.544883 0.383442
1 2011 1 0.423655 0.791725
2 2011 1 0.645894 0.528895

If we have many columns, we could also use a regex to find our
stubnames and pass that list on to wide_to_long
Expand All @@ -359,7 +355,7 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix=r'\d+'):
... r'[A-B]\(.*\)').values if match != [] ])
... )
>>> list(stubnames)
['A(quarterly)', 'B(quarterly)']
['A(weekly)', 'B(weekly)']

All of the above examples have integers as suffixes. It is possible to
have non-integers as suffixes.
Expand All @@ -371,19 +367,19 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix=r'\d+'):
... 'ht_two': [3.4, 3.8, 2.9, 3.2, 2.8, 2.4, 3.3, 3.4, 2.9]
... })
>>> df
birth famid ht_one ht_two
famid birth ht_one ht_two
0 1 1 2.8 3.4
1 2 1 2.9 3.8
2 3 1 2.2 2.9
3 1 2 2.0 3.2
1 1 2 2.9 3.8
2 1 3 2.2 2.9
3 2 1 2.0 3.2
4 2 2 1.8 2.8
5 3 2 1.9 2.4
6 1 3 2.2 3.3
7 2 3 2.3 3.4
5 2 3 1.9 2.4
6 3 1 2.2 3.3
7 3 2 2.3 3.4
8 3 3 2.1 2.9

>>> l = pd.wide_to_long(df, stubnames='ht', i=['famid', 'birth'], j='age',
sep='_', suffix='\w')
... sep='_', suffix='\w+')
>>> l
... # doctest: +NORMALIZE_WHITESPACE
ht
Expand Down