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ENH: add merge indicator to DataFrame.merge #11154

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Sep 20, 2015
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ENH: add merge indicator to DataFrame.merge #11154

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4 changes: 2 additions & 2 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4265,12 +4265,12 @@ def _join_compat(self, other, on=None, how='left', lsuffix='', rsuffix='',
@Appender(_merge_doc, indents=2)
def merge(self, right, how='inner', on=None, left_on=None, right_on=None,
left_index=False, right_index=False, sort=False,
suffixes=('_x', '_y'), copy=True):
suffixes=('_x', '_y'), copy=True, indicator=False):
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is this in the doc-string as well?

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Yeah, they share a docstring.

from pandas.tools.merge import merge
return merge(self, right, how=how, on=on,
left_on=left_on, right_on=right_on,
left_index=left_index, right_index=right_index, sort=sort,
suffixes=suffixes, copy=copy)
suffixes=suffixes, copy=copy, indicator=indicator)

def round(self, decimals=0, out=None):
"""
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42 changes: 30 additions & 12 deletions pandas/tools/tests/test_merge.py
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Expand Up @@ -951,25 +951,27 @@ def test_indicator(self):
df1 = pd.DataFrame({'col1':[0,1], 'col_left':['a','b'], 'col_conflict':[1,2]})
df1_copy = df1.copy()

df2 = pd.DataFrame({'col1':[1,2,3,4,5],'col_right':[2,2,2,2,2],
df2 = pd.DataFrame({'col1':[1,2,3,4,5],'col_right':[2,2,2,2,2],
'col_conflict':[1,2,3,4,5]})
df2_copy = df2.copy()
df_result = pd.DataFrame({'col1':[0,1,2,3,4,5],

df_result = pd.DataFrame({'col1':[0,1,2,3,4,5],
'col_conflict_x':[1,2,np.nan,np.nan,np.nan,np.nan],
'col_left':['a','b', np.nan,np.nan,np.nan,np.nan],
'col_conflict_y':[np.nan,1,2,3,4,5],
'col_left':['a','b', np.nan,np.nan,np.nan,np.nan],
'col_conflict_y':[np.nan,1,2,3,4,5],
'col_right':[np.nan, 2,2,2,2,2]},
dtype='float64')
df_result['_merge'] = pd.Categorical(['left_only','both','right_only',
'right_only','right_only','right_only']
, categories=['left_only', 'right_only', 'both'])

df_result = df_result[['col1', 'col_conflict_x', 'col_left',
df_result = df_result[['col1', 'col_conflict_x', 'col_left',
'col_conflict_y', 'col_right', '_merge' ]]

test = pd.merge(df1, df2, on='col1', how='outer', indicator=True)
assert_frame_equal(test, df_result)
test = df1.merge(df2, on='col1', how='outer', indicator=True)
assert_frame_equal(test, df_result)

# No side effects
assert_frame_equal(df1, df1_copy)
Expand All @@ -981,49 +983,65 @@ def test_indicator(self):

test_custom_name = pd.merge(df1, df2, on='col1', how='outer', indicator='custom_name')
assert_frame_equal(test_custom_name, df_result_custom_name)
test_custom_name = df1.merge(df2, on='col1', how='outer', indicator='custom_name')
assert_frame_equal(test_custom_name, df_result_custom_name)

# Check only accepts strings and booleans
with tm.assertRaises(ValueError):
pd.merge(df1, df2, on='col1', how='outer', indicator=5)
with tm.assertRaises(ValueError):
df1.merge(df2, on='col1', how='outer', indicator=5)

# Check result integrity

test2 = pd.merge(df1, df2, on='col1', how='left', indicator=True)
self.assertTrue((test2._merge != 'right_only').all())
test2 = df1.merge(df2, on='col1', how='left', indicator=True)
self.assertTrue((test2._merge != 'right_only').all())

test3 = pd.merge(df1, df2, on='col1', how='right', indicator=True)
self.assertTrue((test3._merge != 'left_only').all())
test3 = df1.merge(df2, on='col1', how='right', indicator=True)
self.assertTrue((test3._merge != 'left_only').all())

test4 = pd.merge(df1, df2, on='col1', how='inner', indicator=True)
self.assertTrue((test4._merge == 'both').all())
test4 = df1.merge(df2, on='col1', how='inner', indicator=True)
self.assertTrue((test4._merge == 'both').all())

# Check if working name in df
for i in ['_right_indicator', '_left_indicator', '_merge']:
df_badcolumn = pd.DataFrame({'col1':[1,2], i:[2,2]})

with tm.assertRaises(ValueError):
pd.merge(df1, df_badcolumn, on='col1', how='outer', indicator=True)
with tm.assertRaises(ValueError):
df1.merge(df_badcolumn, on='col1', how='outer', indicator=True)

# Check for name conflict with custom name
df_badcolumn = pd.DataFrame({'col1':[1,2], 'custom_column_name':[2,2]})

with tm.assertRaises(ValueError):
pd.merge(df1, df_badcolumn, on='col1', how='outer', indicator='custom_column_name')
with tm.assertRaises(ValueError):
df1.merge(df_badcolumn, on='col1', how='outer', indicator='custom_column_name')

# Merge on multiple columns
df3 = pd.DataFrame({'col1':[0,1], 'col2':['a','b']})

df4 = pd.DataFrame({'col1':[1,1,3], 'col2':['b','x','y']})

hand_coded_result = pd.DataFrame({'col1':[0,1,1,3.0],
hand_coded_result = pd.DataFrame({'col1':[0,1,1,3.0],
'col2':['a','b','x','y']})
hand_coded_result['_merge'] = pd.Categorical(
['left_only','both','right_only','right_only']
, categories=['left_only', 'right_only', 'both'])

test5 = pd.merge(df3, df4, on=['col1', 'col2'], how='outer', indicator=True)
assert_frame_equal(test5, hand_coded_result)

test5 = df3.merge(df4, on=['col1', 'col2'], how='outer', indicator=True)
assert_frame_equal(test5, hand_coded_result)


def _check_merge(x, y):
for how in ['inner', 'left', 'outer']:
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