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get_dummies to select string dtype in addition to object and categorical #45516

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Jan 28, 2022
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get_dummies to select string dtype in addition to object and categorical #45516

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get_dummies to select string dtype in addition to object and categorical
lukemanley Jan 21, 2022
a221491
whatsnew
lukemanley Jan 21, 2022
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4 changes: 2 additions & 2 deletions pandas/core/reshape/reshape.py
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Original file line number Diff line number Diff line change
Expand Up @@ -838,7 +838,7 @@ def get_dummies(
columns : list-like, default None
Column names in the DataFrame to be encoded.
If `columns` is None then all the columns with
`object` or `category` dtype will be converted.
`object`, `string`, or `category` dtype will be converted.
sparse : bool, default False
Whether the dummy-encoded columns should be backed by
a :class:`SparseArray` (True) or a regular NumPy array (False).
Expand Down Expand Up @@ -915,7 +915,7 @@ def get_dummies(
"""
from pandas.core.reshape.concat import concat

dtypes_to_encode = ["object", "category"]
dtypes_to_encode = ["object", "string", "category"]

if isinstance(data, DataFrame):
# determine columns being encoded
Expand Down
16 changes: 16 additions & 0 deletions pandas/tests/reshape/test_get_dummies.py
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Expand Up @@ -196,6 +196,22 @@ def test_dataframe_dummies_all_obj(self, df, sparse):

tm.assert_frame_equal(result, expected)

def test_dataframe_dummies_string_dtype(self, df):
# GH44965
df = df[["A", "B"]]
df = df.astype({"A": "object", "B": "string"})
result = get_dummies(df)
expected = DataFrame(
{
"A_a": [1, 0, 1],
"A_b": [0, 1, 0],
"B_b": [1, 1, 0],
"B_c": [0, 0, 1],
},
dtype=np.uint8,
)
tm.assert_frame_equal(result, expected)

def test_dataframe_dummies_mix_default(self, df, sparse, dtype):
result = get_dummies(df, sparse=sparse, dtype=dtype)
if sparse:
Expand Down