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BUG: Crosstab margins ignoring dropna #12614

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BUG: Crosstab margins ignoring dropna #12614

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9c0d99b
Modified _generate_marginal_results
OXPHOS Mar 14, 2016
7c28949
change in pivot_table-if margin
Mar 14, 2016
0039da5
Documentaion
Mar 14, 2016
76fbacf
Fix stylistic errors
OXPHOS Mar 15, 2016
869a253
Fixed margin=true, dropna=false error
OXPHOS Mar 16, 2016
d3ed27a
Update what's new
OXPHOS Mar 16, 2016
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12 changes: 9 additions & 3 deletions pandas/tools/pivot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -149,9 +149,15 @@ def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
table = table.fillna(value=fill_value, downcast='infer')

if margins:
table = _add_margins(table, data, values, rows=index,
cols=columns, aggfunc=aggfunc,
margins_name=margins_name)
if dropna:
data_dropna = data[data.notnull().all(axis = 1)]
table = _add_margins(table, data_dropna, values, rows=index,
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you don't need to repeat the if, just do:

if dropna:
   data = data[......]

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You mean like below? I felt unsafe changing data values but if you're okay with it I'll update the codes.

if dropna: data = data[data.notnull().all(axis = 1)] table = _add_margins(table, data, values, rows=index, cols=columns, aggfunc=aggfunc, margins_name=margins_name)

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how are you changing data values?

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I think she means over-writing data. That's fine if all tests clear!

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Got it. Thanks!

cols=columns, aggfunc=aggfunc,
margins_name=margins_name)
else:
table = _add_margins(table, data, values, rows=index,
cols=columns, aggfunc=aggfunc,
margins_name=margins_name)

# discard the top level
if values_passed and not values_multi and not table.empty:
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23 changes: 23 additions & 0 deletions pandas/tools/tests/test_pivot.py
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Expand Up @@ -935,6 +935,29 @@ def test_crosstab_no_overlap(self):
expected = pd.DataFrame()

tm.assert_frame_equal(actual, expected)

def test_margin_ignore_dropna_bug(self):
# Bug#12577
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give a small descrption of the problem as well (in a comment)

df = pd.DataFrame({'a': [1, 2, 2, 2, 2, np.nan], 'b': [3, 3, 4, 4, 4, 4]})
actual = pd.crosstab(df.a,df.b, margins=True)
expected = pd.DataFrame([[1, 0, 1], [1, 3, 4], [2, 3, 5]])
expected.index = Index([1.0, 2.0, 'All'], name = 'a')
expected.columns = Index([3, 4, 'All'], name = 'b')
tm.assert_frame_equal(actual, expected)

df = DataFrame({'a':[1, np.nan, np.nan, np.nan, 2, np.nan], 'b':[3, np.nan, 4, 4, 4, 4]})
actual = pd.crosstab(df.a,df.b, margins=True)
expected = pd.DataFrame([[1, 0, 1], [0, 1, 1], [1, 1, 2]])
expected.index = Index([1.0, 2.0, 'All'], name = 'a')
expected.columns = Index([3.0, 4.0, 'All'], name = 'b')
tm.assert_frame_equal(actual, expected)

df = DataFrame({'a':[1, np.nan, np.nan, np.nan, np.nan, 2], 'b':[3, 3, 4, 4, 4, 4]})
actual = pd.crosstab(df.a,df.b, margins=True)
expected = pd.DataFrame([[1, 0, 1], [0, 1, 1], [1, 1, 2]])
expected.index = Index([1.0, 2.0, 'All'], name = 'a')
expected.columns = Index([3, 4, 'All'], name = 'b')
tm.assert_frame_equal(actual, expected)

if __name__ == '__main__':
import nose
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