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"""
Tests dtype specification during parsing
for all of the parsers defined in parsers.py
"""
from io import StringIO
import numpy as np
import pytest
from pandas import (
Categorical,
DataFrame,
Index,
MultiIndex,
Series,
concat,
)
import pandas._testing as tm
# TODO(1.4): Change me into individual xfails at release time
pytestmark = pytest.mark.usefixtures("pyarrow_skip")
def test_dtype_all_columns_empty(all_parsers):
# see gh-12048
parser = all_parsers
result = parser.read_csv(StringIO("A,B"), dtype=str)
expected = DataFrame({"A": [], "B": []}, dtype=str)
tm.assert_frame_equal(result, expected)
def test_empty_pass_dtype(all_parsers):
parser = all_parsers
data = "one,two"
result = parser.read_csv(StringIO(data), dtype={"one": "u1"})
expected = DataFrame(
{"one": np.empty(0, dtype="u1"), "two": np.empty(0, dtype=object)},
)
tm.assert_frame_equal(result, expected)
def test_empty_with_index_pass_dtype(all_parsers):
parser = all_parsers
data = "one,two"
result = parser.read_csv(
StringIO(data), index_col=["one"], dtype={"one": "u1", 1: "f"}
)
expected = DataFrame(
{"two": np.empty(0, dtype="f")}, index=Index([], dtype="u1", name="one")
)
tm.assert_frame_equal(result, expected)
def test_empty_with_multi_index_pass_dtype(all_parsers):
parser = all_parsers
data = "one,two,three"
result = parser.read_csv(
StringIO(data), index_col=["one", "two"], dtype={"one": "u1", 1: "f8"}
)
exp_idx = MultiIndex.from_arrays(
[np.empty(0, dtype="u1"), np.empty(0, dtype=np.float64)],
names=["one", "two"],
)
expected = DataFrame({"three": np.empty(0, dtype=object)}, index=exp_idx)
tm.assert_frame_equal(result, expected)
def test_empty_with_mangled_column_pass_dtype_by_names(all_parsers):
parser = all_parsers
data = "one,one"
result = parser.read_csv(StringIO(data), dtype={"one": "u1", "one.1": "f"})
expected = DataFrame(
{"one": np.empty(0, dtype="u1"), "one.1": np.empty(0, dtype="f")},
)
tm.assert_frame_equal(result, expected)
def test_empty_with_mangled_column_pass_dtype_by_indexes(all_parsers):
parser = all_parsers
data = "one,one"
result = parser.read_csv(StringIO(data), dtype={0: "u1", 1: "f"})
expected = DataFrame(
{"one": np.empty(0, dtype="u1"), "one.1": np.empty(0, dtype="f")},
)
tm.assert_frame_equal(result, expected)
def test_empty_with_dup_column_pass_dtype_by_indexes(all_parsers):
# see gh-9424
parser = all_parsers
expected = concat(
[Series([], name="one", dtype="u1"), Series([], name="one.1", dtype="f")],
axis=1,
)
data = "one,one"
result = parser.read_csv(StringIO(data), dtype={0: "u1", 1: "f"})
tm.assert_frame_equal(result, expected)
def test_empty_with_dup_column_pass_dtype_by_indexes_raises(all_parsers):
# see gh-9424
parser = all_parsers
expected = concat(
[Series([], name="one", dtype="u1"), Series([], name="one.1", dtype="f")],
axis=1,
)
expected.index = expected.index.astype(object)
with pytest.raises(ValueError, match="Duplicate names"):
data = ""
parser.read_csv(StringIO(data), names=["one", "one"], dtype={0: "u1", 1: "f"})
@pytest.mark.parametrize(
"dtype,expected",
[
(np.float64, DataFrame(columns=["a", "b"], dtype=np.float64)),
(
"category",
DataFrame({"a": Categorical([]), "b": Categorical([])}),
),
(
{"a": "category", "b": "category"},
DataFrame({"a": Categorical([]), "b": Categorical([])}),
),
("datetime64[ns]", DataFrame(columns=["a", "b"], dtype="datetime64[ns]")),
(
"timedelta64[ns]",
DataFrame(
{
"a": Series([], dtype="timedelta64[ns]"),
"b": Series([], dtype="timedelta64[ns]"),
},
),
),
(
{"a": np.int64, "b": np.int32},
DataFrame(
{"a": Series([], dtype=np.int64), "b": Series([], dtype=np.int32)},
),
),
(
{0: np.int64, 1: np.int32},
DataFrame(
{"a": Series([], dtype=np.int64), "b": Series([], dtype=np.int32)},
),
),
(
{"a": np.int64, 1: np.int32},
DataFrame(
{"a": Series([], dtype=np.int64), "b": Series([], dtype=np.int32)},
),
),
],
)
def test_empty_dtype(all_parsers, dtype, expected):
# see gh-14712
parser = all_parsers
data = "a,b"
result = parser.read_csv(StringIO(data), header=0, dtype=dtype)
tm.assert_frame_equal(result, expected)