Alle Dateien aus dem Pythonkurs
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 

150 lines
3.7 KiB

"""
Tests the usecols functionality during parsing
for all of the parsers defined in parsers.py
"""
from io import StringIO
import pytest
from pandas import (
DataFrame,
Index,
Timestamp,
)
import pandas._testing as tm
# TODO(1.4): Change these to xfails whenever parse_dates support(which was
# intentionally disable to keep small PR sizes) is added back
pytestmark = pytest.mark.usefixtures("pyarrow_skip")
@pytest.mark.parametrize("usecols", [[0, 2, 3], [3, 0, 2]])
def test_usecols_with_parse_dates(all_parsers, usecols):
# see gh-9755
data = """a,b,c,d,e
0,1,2014-01-01,09:00,4
0,1,2014-01-02,10:00,4"""
parser = all_parsers
parse_dates = [[1, 2]]
cols = {
"a": [0, 0],
"c_d": [Timestamp("2014-01-01 09:00:00"), Timestamp("2014-01-02 10:00:00")],
}
expected = DataFrame(cols, columns=["c_d", "a"])
result = parser.read_csv(StringIO(data), usecols=usecols, parse_dates=parse_dates)
tm.assert_frame_equal(result, expected)
def test_usecols_with_parse_dates2(all_parsers):
# see gh-13604
parser = all_parsers
data = """2008-02-07 09:40,1032.43
2008-02-07 09:50,1042.54
2008-02-07 10:00,1051.65"""
names = ["date", "values"]
usecols = names[:]
parse_dates = [0]
index = Index(
[
Timestamp("2008-02-07 09:40"),
Timestamp("2008-02-07 09:50"),
Timestamp("2008-02-07 10:00"),
],
name="date",
)
cols = {"values": [1032.43, 1042.54, 1051.65]}
expected = DataFrame(cols, index=index)
result = parser.read_csv(
StringIO(data),
parse_dates=parse_dates,
index_col=0,
usecols=usecols,
header=None,
names=names,
)
tm.assert_frame_equal(result, expected)
def test_usecols_with_parse_dates3(all_parsers):
# see gh-14792
parser = all_parsers
data = """a,b,c,d,e,f,g,h,i,j
2016/09/21,1,1,2,3,4,5,6,7,8"""
usecols = list("abcdefghij")
parse_dates = [0]
cols = {
"a": Timestamp("2016-09-21").as_unit("ns"),
"b": [1],
"c": [1],
"d": [2],
"e": [3],
"f": [4],
"g": [5],
"h": [6],
"i": [7],
"j": [8],
}
expected = DataFrame(cols, columns=usecols)
result = parser.read_csv(StringIO(data), usecols=usecols, parse_dates=parse_dates)
tm.assert_frame_equal(result, expected)
def test_usecols_with_parse_dates4(all_parsers):
data = "a,b,c,d,e,f,g,h,i,j\n2016/09/21,1,1,2,3,4,5,6,7,8"
usecols = list("abcdefghij")
parse_dates = [[0, 1]]
parser = all_parsers
cols = {
"a_b": "2016/09/21 1",
"c": [1],
"d": [2],
"e": [3],
"f": [4],
"g": [5],
"h": [6],
"i": [7],
"j": [8],
}
expected = DataFrame(cols, columns=["a_b"] + list("cdefghij"))
result = parser.read_csv(
StringIO(data),
usecols=usecols,
parse_dates=parse_dates,
)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize("usecols", [[0, 2, 3], [3, 0, 2]])
@pytest.mark.parametrize(
"names",
[
list("abcde"), # Names span all columns in original data.
list("acd"), # Names span only the selected columns.
],
)
def test_usecols_with_parse_dates_and_names(all_parsers, usecols, names):
# see gh-9755
s = """0,1,2014-01-01,09:00,4
0,1,2014-01-02,10:00,4"""
parse_dates = [[1, 2]]
parser = all_parsers
cols = {
"a": [0, 0],
"c_d": [Timestamp("2014-01-01 09:00:00"), Timestamp("2014-01-02 10:00:00")],
}
expected = DataFrame(cols, columns=["c_d", "a"])
result = parser.read_csv(
StringIO(s), names=names, parse_dates=parse_dates, usecols=usecols
)
tm.assert_frame_equal(result, expected)