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TST: moved file test_concat.py to folder ./concat/ (#37243) #37360

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Merged
merged 7 commits into from
Oct 23, 2020
Merged

TST: moved file test_concat.py to folder ./concat/ (#37243) #37360

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4cfa5a0
TST: moved file test_concat.py to folder ./concat/ (#37243)
kamilt5 Oct 23, 2020
bf3030d
splitted class TestAppendCommon to file test_append_common.py
kamilt5 Oct 23, 2020
1b96b30
splitted class TestAppend to file test_append.py
kamilt5 Oct 23, 2020
7b7d0a9
split class TestAppend to file test_append.py
kamilt5 Oct 23, 2020
50d4254
split class TestDataFrameConcat to file test_dataframe.py
kamilt5 Oct 23, 2020
b78767e
pre-commit fixes
kamilt5 Oct 23, 2020
7f126e4
Merge branch 'master' into i37243_move_files
kamilt5 Oct 23, 2020
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118 changes: 0 additions & 118 deletions pandas/tests/reshape/concat/test_concat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1845,124 +1845,6 @@ def test_concat_preserves_extension_int64_dtype():
tm.assert_frame_equal(result, expected)

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There is typo in commit message, it should be "split class TestSeriesConcat to file test_series.py"


class TestSeriesConcat:
@pytest.mark.parametrize(
"dtype", ["float64", "int8", "uint8", "bool", "m8[ns]", "M8[ns]"]
)
def test_concat_empty_series_dtypes_match_roundtrips(self, dtype):
dtype = np.dtype(dtype)

result = pd.concat([Series(dtype=dtype)])
assert result.dtype == dtype

result = pd.concat([Series(dtype=dtype), Series(dtype=dtype)])
assert result.dtype == dtype

def test_concat_empty_series_dtypes_roundtrips(self):

# round-tripping with self & like self
dtypes = map(np.dtype, ["float64", "int8", "uint8", "bool", "m8[ns]", "M8[ns]"])

def int_result_type(dtype, dtype2):
typs = {dtype.kind, dtype2.kind}
if not len(typs - {"i", "u", "b"}) and (
dtype.kind == "i" or dtype2.kind == "i"
):
return "i"
elif not len(typs - {"u", "b"}) and (
dtype.kind == "u" or dtype2.kind == "u"
):
return "u"
return None

def float_result_type(dtype, dtype2):
typs = {dtype.kind, dtype2.kind}
if not len(typs - {"f", "i", "u"}) and (
dtype.kind == "f" or dtype2.kind == "f"
):
return "f"
return None

def get_result_type(dtype, dtype2):
result = float_result_type(dtype, dtype2)
if result is not None:
return result
result = int_result_type(dtype, dtype2)
if result is not None:
return result
return "O"

for dtype in dtypes:
for dtype2 in dtypes:
if dtype == dtype2:
continue

expected = get_result_type(dtype, dtype2)
result = pd.concat([Series(dtype=dtype), Series(dtype=dtype2)]).dtype
assert result.kind == expected

@pytest.mark.parametrize(
"left,right,expected",
[
# booleans
(np.bool_, np.int32, np.int32),
(np.bool_, np.float32, np.object_),
# datetime-like
("m8[ns]", np.bool_, np.object_),
("m8[ns]", np.int64, np.object_),
("M8[ns]", np.bool_, np.object_),
("M8[ns]", np.int64, np.object_),
# categorical
("category", "category", "category"),
("category", "object", "object"),
],
)
def test_concat_empty_series_dtypes(self, left, right, expected):
result = pd.concat([Series(dtype=left), Series(dtype=right)])
assert result.dtype == expected

def test_concat_empty_series_dtypes_triple(self):

assert (
pd.concat(
[Series(dtype="M8[ns]"), Series(dtype=np.bool_), Series(dtype=np.int64)]
).dtype
== np.object_
)

def test_concat_empty_series_dtype_category_with_array(self):
# GH#18515
assert (
pd.concat(
[Series(np.array([]), dtype="category"), Series(dtype="float64")]
).dtype
== "float64"
)

def test_concat_empty_series_dtypes_sparse(self):
result = pd.concat(
[
Series(dtype="float64").astype("Sparse"),
Series(dtype="float64").astype("Sparse"),
]
)
assert result.dtype == "Sparse[float64]"

result = pd.concat(
[Series(dtype="float64").astype("Sparse"), Series(dtype="float64")]
)
# TODO: release-note: concat sparse dtype
expected = pd.SparseDtype(np.float64)
assert result.dtype == expected

result = pd.concat(
[Series(dtype="float64").astype("Sparse"), Series(dtype="object")]
)
# TODO: release-note: concat sparse dtype
expected = pd.SparseDtype("object")
assert result.dtype == expected


class TestDataFrameConcat:
def test_concat_multiple_frames_dtypes(self):

Expand Down
125 changes: 125 additions & 0 deletions pandas/tests/reshape/concat/test_series.py
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Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,125 @@
import numpy as np
import pytest

import pandas as pd
from pandas import (
Series,
)


class TestSeriesConcat:
@pytest.mark.parametrize(
"dtype", ["float64", "int8", "uint8", "bool", "m8[ns]", "M8[ns]"]
)
def test_concat_empty_series_dtypes_match_roundtrips(self, dtype):
dtype = np.dtype(dtype)

result = pd.concat([Series(dtype=dtype)])
assert result.dtype == dtype

result = pd.concat([Series(dtype=dtype), Series(dtype=dtype)])
assert result.dtype == dtype

def test_concat_empty_series_dtypes_roundtrips(self):

# round-tripping with self & like self
dtypes = map(np.dtype, ["float64", "int8", "uint8", "bool", "m8[ns]", "M8[ns]"])

def int_result_type(dtype, dtype2):
typs = {dtype.kind, dtype2.kind}
if not len(typs - {"i", "u", "b"}) and (
dtype.kind == "i" or dtype2.kind == "i"
):
return "i"
elif not len(typs - {"u", "b"}) and (
dtype.kind == "u" or dtype2.kind == "u"
):
return "u"
return None

def float_result_type(dtype, dtype2):
typs = {dtype.kind, dtype2.kind}
if not len(typs - {"f", "i", "u"}) and (
dtype.kind == "f" or dtype2.kind == "f"
):
return "f"
return None

def get_result_type(dtype, dtype2):
result = float_result_type(dtype, dtype2)
if result is not None:
return result
result = int_result_type(dtype, dtype2)
if result is not None:
return result
return "O"

for dtype in dtypes:
for dtype2 in dtypes:
if dtype == dtype2:
continue

expected = get_result_type(dtype, dtype2)
result = pd.concat([Series(dtype=dtype), Series(dtype=dtype2)]).dtype
assert result.kind == expected

@pytest.mark.parametrize(
"left,right,expected",
[
# booleans
(np.bool_, np.int32, np.int32),
(np.bool_, np.float32, np.object_),
# datetime-like
("m8[ns]", np.bool_, np.object_),
("m8[ns]", np.int64, np.object_),
("M8[ns]", np.bool_, np.object_),
("M8[ns]", np.int64, np.object_),
# categorical
("category", "category", "category"),
("category", "object", "object"),
],
)
def test_concat_empty_series_dtypes(self, left, right, expected):
result = pd.concat([Series(dtype=left), Series(dtype=right)])
assert result.dtype == expected

def test_concat_empty_series_dtypes_triple(self):

assert (
pd.concat(
[Series(dtype="M8[ns]"), Series(dtype=np.bool_), Series(dtype=np.int64)]
).dtype
== np.object_
)

def test_concat_empty_series_dtype_category_with_array(self):
# GH#18515
assert (
pd.concat(
[Series(np.array([]), dtype="category"), Series(dtype="float64")]
).dtype
== "float64"
)

def test_concat_empty_series_dtypes_sparse(self):
result = pd.concat(
[
Series(dtype="float64").astype("Sparse"),
Series(dtype="float64").astype("Sparse"),
]
)
assert result.dtype == "Sparse[float64]"

result = pd.concat(
[Series(dtype="float64").astype("Sparse"), Series(dtype="float64")]
)
# TODO: release-note: concat sparse dtype
expected = pd.SparseDtype(np.float64)
assert result.dtype == expected

result = pd.concat(
[Series(dtype="float64").astype("Sparse"), Series(dtype="object")]
)
# TODO: release-note: concat sparse dtype
expected = pd.SparseDtype("object")
assert result.dtype == expected