ai-content-maker/.venv/Lib/site-packages/pandas/tests/io/parser/test_converters.py

204 lines
4.9 KiB
Python

"""
Tests column conversion functionality during parsing
for all of the parsers defined in parsers.py
"""
from io import StringIO
from dateutil.parser import parse
import numpy as np
import pytest
import pandas as pd
from pandas import (
DataFrame,
Index,
)
import pandas._testing as tm
pytestmark = pytest.mark.usefixtures("pyarrow_skip")
def test_converters_type_must_be_dict(all_parsers):
parser = all_parsers
data = """index,A,B,C,D
foo,2,3,4,5
"""
with pytest.raises(TypeError, match="Type converters.+"):
parser.read_csv(StringIO(data), converters=0)
@pytest.mark.parametrize("column", [3, "D"])
@pytest.mark.parametrize(
"converter", [parse, lambda x: int(x.split("/")[2])] # Produce integer.
)
def test_converters(all_parsers, column, converter):
parser = all_parsers
data = """A,B,C,D
a,1,2,01/01/2009
b,3,4,01/02/2009
c,4,5,01/03/2009
"""
result = parser.read_csv(StringIO(data), converters={column: converter})
expected = parser.read_csv(StringIO(data))
expected["D"] = expected["D"].map(converter)
tm.assert_frame_equal(result, expected)
def test_converters_no_implicit_conv(all_parsers):
# see gh-2184
parser = all_parsers
data = """000102,1.2,A\n001245,2,B"""
converters = {0: lambda x: x.strip()}
result = parser.read_csv(StringIO(data), header=None, converters=converters)
# Column 0 should not be casted to numeric and should remain as object.
expected = DataFrame([["000102", 1.2, "A"], ["001245", 2, "B"]])
tm.assert_frame_equal(result, expected)
def test_converters_euro_decimal_format(all_parsers):
# see gh-583
converters = {}
parser = all_parsers
data = """Id;Number1;Number2;Text1;Text2;Number3
1;1521,1541;187101,9543;ABC;poi;4,7387
2;121,12;14897,76;DEF;uyt;0,3773
3;878,158;108013,434;GHI;rez;2,7356"""
converters["Number1"] = converters["Number2"] = converters[
"Number3"
] = lambda x: float(x.replace(",", "."))
result = parser.read_csv(StringIO(data), sep=";", converters=converters)
expected = DataFrame(
[
[1, 1521.1541, 187101.9543, "ABC", "poi", 4.7387],
[2, 121.12, 14897.76, "DEF", "uyt", 0.3773],
[3, 878.158, 108013.434, "GHI", "rez", 2.7356],
],
columns=["Id", "Number1", "Number2", "Text1", "Text2", "Number3"],
)
tm.assert_frame_equal(result, expected)
def test_converters_corner_with_nans(all_parsers):
parser = all_parsers
data = """id,score,days
1,2,12
2,2-5,
3,,14+
4,6-12,2"""
# Example converters.
def convert_days(x):
x = x.strip()
if not x:
return np.nan
is_plus = x.endswith("+")
if is_plus:
x = int(x[:-1]) + 1
else:
x = int(x)
return x
def convert_days_sentinel(x):
x = x.strip()
if not x:
return np.nan
is_plus = x.endswith("+")
if is_plus:
x = int(x[:-1]) + 1
else:
x = int(x)
return x
def convert_score(x):
x = x.strip()
if not x:
return np.nan
if x.find("-") > 0:
val_min, val_max = map(int, x.split("-"))
val = 0.5 * (val_min + val_max)
else:
val = float(x)
return val
results = []
for day_converter in [convert_days, convert_days_sentinel]:
result = parser.read_csv(
StringIO(data),
converters={"score": convert_score, "days": day_converter},
na_values=["", None],
)
assert pd.isna(result["days"][1])
results.append(result)
tm.assert_frame_equal(results[0], results[1])
@pytest.mark.parametrize("conv_f", [lambda x: x, str])
def test_converter_index_col_bug(all_parsers, conv_f):
# see gh-1835 , GH#40589
parser = all_parsers
data = "A;B\n1;2\n3;4"
rs = parser.read_csv(
StringIO(data), sep=";", index_col="A", converters={"A": conv_f}
)
xp = DataFrame({"B": [2, 4]}, index=Index(["1", "3"], name="A", dtype="object"))
tm.assert_frame_equal(rs, xp)
def test_converter_identity_object(all_parsers):
# GH#40589
parser = all_parsers
data = "A,B\n1,2\n3,4"
rs = parser.read_csv(StringIO(data), converters={"A": lambda x: x})
xp = DataFrame({"A": ["1", "3"], "B": [2, 4]})
tm.assert_frame_equal(rs, xp)
def test_converter_multi_index(all_parsers):
# GH 42446
parser = all_parsers
data = "A,B,B\nX,Y,Z\n1,2,3"
result = parser.read_csv(
StringIO(data),
header=list(range(2)),
converters={
("A", "X"): np.int32,
("B", "Y"): np.int32,
("B", "Z"): np.float32,
},
)
expected = DataFrame(
{
("A", "X"): np.int32([1]),
("B", "Y"): np.int32([2]),
("B", "Z"): np.float32([3]),
}
)
tm.assert_frame_equal(result, expected)