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Fix the output of df.describe on an empty categorical / object column #26474

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Merged
merged 10 commits into from
Jun 1, 2019
Merged

Fix the output of df.describe on an empty categorical / object column #26474

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d35c39a
BUG: Ensure that top and freq are reported as None for empty dataframes
enisnazif May 19, 2019
e7a7bdf
BUG: Ensure that the index values obtained when calling describe on a…
enisnazif May 20, 2019
10df157
BUG: Ensure that the index values obtained when calling describe on a…
enisnazif May 20, 2019
1c7b6d1
BUG: Ensure that the index values obtained when calling describe on a…
enisnazif May 20, 2019
302b28c
BUG: Ensure that the index values obtained when calling describe on a…
enisnazif May 26, 2019
65b1cc9
Add entry to api_breaking section for 0.25.0
enisnazif May 26, 2019
41a9c36
Update v0.25.0.rst
enisnazif May 30, 2019
55702b2
fixup
TomAugspurger May 30, 2019
8021619
Merge remote-tracking branch 'upstream/master' into enisnazif-fix-emp…
TomAugspurger May 30, 2019
7100855
Merge remote-tracking branch 'upstream/master' into enisnazif-fix-emp…
TomAugspurger May 31, 2019
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2 changes: 1 addition & 1 deletion pandas/core/arrays/categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1477,7 +1477,7 @@ def value_counts(self, dropna=True):

if dropna or clean:
obs = code if clean else code[mask]
count = bincount(obs, minlength=ncat or None)
count = bincount(obs, minlength=ncat or 0)
else:
count = bincount(np.where(mask, code, ncat))
ix = np.append(ix, -1)
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6 changes: 6 additions & 0 deletions pandas/core/generic.py
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Expand Up @@ -9920,6 +9920,12 @@ def describe_categorical_1d(data):
names += ['top', 'freq']
result += [top, freq]

# If the DataFrame is empty, set 'top' and 'freq' to None
# to maintain output shape consistency
else:
names += ['top', 'freq']
result += [None, None]

return pd.Series(result, index=names, name=data.name)

def describe_1d(data):
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9 changes: 9 additions & 0 deletions pandas/tests/frame/test_analytics.py
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Expand Up @@ -588,6 +588,14 @@ def test_describe_categorical(self):
result = df3.describe()
tm.assert_numpy_array_equal(result["cat"].values, result["s"].values)

# Ensure the index of an an empty categoric DataFrame column
# also contains (count, unique, top, freq)
df = pd.DataFrame({"empty_col": Categorical([])})
result = df.describe()
expected = DataFrame({'empty_col': [0, 0, None, None]},
index=['count', 'unique', 'top', 'freq'])
tm.assert_frame_equal(result, expected)

def test_describe_categorical_columns(self):
# GH 11558
columns = pd.CategoricalIndex(['int1', 'int2', 'obj'],
Expand All @@ -608,6 +616,7 @@ def test_describe_categorical_columns(self):
index=['count', 'mean', 'std', 'min', '25%',
'50%', '75%', 'max'],
columns=exp_columns)

tm.assert_frame_equal(result, expected)
tm.assert_categorical_equal(result.columns.values,
expected.columns.values)
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