mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-11-27 01:08:12 +01:00
242 lines
8 KiB
Python
242 lines
8 KiB
Python
from datetime import datetime
|
||
from io import StringIO
|
||
|
||
import numpy as np
|
||
import pytest
|
||
|
||
import pandas as pd
|
||
from pandas import DataFrame, Series
|
||
import pandas._testing as tm
|
||
|
||
from pandas.io.common import get_handle
|
||
|
||
|
||
class TestSeriesToCSV:
|
||
def read_csv(self, path, **kwargs):
|
||
params = dict(squeeze=True, index_col=0, header=None, parse_dates=True)
|
||
params.update(**kwargs)
|
||
|
||
header = params.get("header")
|
||
out = pd.read_csv(path, **params)
|
||
|
||
if header is None:
|
||
out.name = out.index.name = None
|
||
|
||
return out
|
||
|
||
def test_from_csv(self, datetime_series, string_series):
|
||
# freq doesnt round-trip
|
||
datetime_series.index = datetime_series.index._with_freq(None)
|
||
|
||
with tm.ensure_clean() as path:
|
||
datetime_series.to_csv(path, header=False)
|
||
ts = self.read_csv(path)
|
||
tm.assert_series_equal(datetime_series, ts, check_names=False)
|
||
|
||
assert ts.name is None
|
||
assert ts.index.name is None
|
||
|
||
# see gh-10483
|
||
datetime_series.to_csv(path, header=True)
|
||
ts_h = self.read_csv(path, header=0)
|
||
assert ts_h.name == "ts"
|
||
|
||
string_series.to_csv(path, header=False)
|
||
series = self.read_csv(path)
|
||
tm.assert_series_equal(string_series, series, check_names=False)
|
||
|
||
assert series.name is None
|
||
assert series.index.name is None
|
||
|
||
string_series.to_csv(path, header=True)
|
||
series_h = self.read_csv(path, header=0)
|
||
assert series_h.name == "series"
|
||
|
||
with open(path, "w") as outfile:
|
||
outfile.write("1998-01-01|1.0\n1999-01-01|2.0")
|
||
|
||
series = self.read_csv(path, sep="|")
|
||
check_series = Series(
|
||
{datetime(1998, 1, 1): 1.0, datetime(1999, 1, 1): 2.0}
|
||
)
|
||
tm.assert_series_equal(check_series, series)
|
||
|
||
series = self.read_csv(path, sep="|", parse_dates=False)
|
||
check_series = Series({"1998-01-01": 1.0, "1999-01-01": 2.0})
|
||
tm.assert_series_equal(check_series, series)
|
||
|
||
def test_to_csv(self, datetime_series):
|
||
import io
|
||
|
||
with tm.ensure_clean() as path:
|
||
datetime_series.to_csv(path, header=False)
|
||
|
||
with io.open(path, newline=None) as f:
|
||
lines = f.readlines()
|
||
assert lines[1] != "\n"
|
||
|
||
datetime_series.to_csv(path, index=False, header=False)
|
||
arr = np.loadtxt(path)
|
||
tm.assert_almost_equal(arr, datetime_series.values)
|
||
|
||
def test_to_csv_unicode_index(self):
|
||
buf = StringIO()
|
||
s = Series(["\u05d0", "d2"], index=["\u05d0", "\u05d1"])
|
||
|
||
s.to_csv(buf, encoding="UTF-8", header=False)
|
||
buf.seek(0)
|
||
|
||
s2 = self.read_csv(buf, index_col=0, encoding="UTF-8")
|
||
tm.assert_series_equal(s, s2)
|
||
|
||
def test_to_csv_float_format(self):
|
||
|
||
with tm.ensure_clean() as filename:
|
||
ser = Series([0.123456, 0.234567, 0.567567])
|
||
ser.to_csv(filename, float_format="%.2f", header=False)
|
||
|
||
rs = self.read_csv(filename)
|
||
xp = Series([0.12, 0.23, 0.57])
|
||
tm.assert_series_equal(rs, xp)
|
||
|
||
def test_to_csv_list_entries(self):
|
||
s = Series(["jack and jill", "jesse and frank"])
|
||
|
||
split = s.str.split(r"\s+and\s+")
|
||
|
||
buf = StringIO()
|
||
split.to_csv(buf, header=False)
|
||
|
||
def test_to_csv_path_is_none(self):
|
||
# GH 8215
|
||
# Series.to_csv() was returning None, inconsistent with
|
||
# DataFrame.to_csv() which returned string
|
||
s = Series([1, 2, 3])
|
||
csv_str = s.to_csv(path_or_buf=None, header=False)
|
||
assert isinstance(csv_str, str)
|
||
|
||
@pytest.mark.parametrize(
|
||
"s,encoding",
|
||
[
|
||
(
|
||
Series([0.123456, 0.234567, 0.567567], index=["A", "B", "C"], name="X"),
|
||
None,
|
||
),
|
||
# GH 21241, 21118
|
||
(Series(["abc", "def", "ghi"], name="X"), "ascii"),
|
||
(Series(["123", "你好", "世界"], name="中文"), "gb2312"),
|
||
(Series(["123", "Γειά σου", "Κόσμε"], name="Ελληνικά"), "cp737"),
|
||
],
|
||
)
|
||
def test_to_csv_compression(self, s, encoding, compression):
|
||
|
||
with tm.ensure_clean() as filename:
|
||
|
||
s.to_csv(filename, compression=compression, encoding=encoding, header=True)
|
||
# test the round trip - to_csv -> read_csv
|
||
result = pd.read_csv(
|
||
filename,
|
||
compression=compression,
|
||
encoding=encoding,
|
||
index_col=0,
|
||
squeeze=True,
|
||
)
|
||
tm.assert_series_equal(s, result)
|
||
|
||
# test the round trip using file handle - to_csv -> read_csv
|
||
f, _handles = get_handle(
|
||
filename, "w", compression=compression, encoding=encoding
|
||
)
|
||
with f:
|
||
s.to_csv(f, encoding=encoding, header=True)
|
||
result = pd.read_csv(
|
||
filename,
|
||
compression=compression,
|
||
encoding=encoding,
|
||
index_col=0,
|
||
squeeze=True,
|
||
)
|
||
tm.assert_series_equal(s, result)
|
||
|
||
# explicitly ensure file was compressed
|
||
with tm.decompress_file(filename, compression) as fh:
|
||
text = fh.read().decode(encoding or "utf8")
|
||
assert s.name in text
|
||
|
||
with tm.decompress_file(filename, compression) as fh:
|
||
tm.assert_series_equal(
|
||
s, pd.read_csv(fh, index_col=0, squeeze=True, encoding=encoding)
|
||
)
|
||
|
||
def test_to_csv_interval_index(self):
|
||
# GH 28210
|
||
s = Series(["foo", "bar", "baz"], index=pd.interval_range(0, 3))
|
||
|
||
with tm.ensure_clean("__tmp_to_csv_interval_index__.csv") as path:
|
||
s.to_csv(path, header=False)
|
||
result = self.read_csv(path, index_col=0, squeeze=True)
|
||
|
||
# can't roundtrip intervalindex via read_csv so check string repr (GH 23595)
|
||
expected = s.copy()
|
||
expected.index = expected.index.astype(str)
|
||
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
class TestSeriesIO:
|
||
def test_to_frame(self, datetime_series):
|
||
datetime_series.name = None
|
||
rs = datetime_series.to_frame()
|
||
xp = pd.DataFrame(datetime_series.values, index=datetime_series.index)
|
||
tm.assert_frame_equal(rs, xp)
|
||
|
||
datetime_series.name = "testname"
|
||
rs = datetime_series.to_frame()
|
||
xp = pd.DataFrame(
|
||
dict(testname=datetime_series.values), index=datetime_series.index
|
||
)
|
||
tm.assert_frame_equal(rs, xp)
|
||
|
||
rs = datetime_series.to_frame(name="testdifferent")
|
||
xp = pd.DataFrame(
|
||
dict(testdifferent=datetime_series.values), index=datetime_series.index
|
||
)
|
||
tm.assert_frame_equal(rs, xp)
|
||
|
||
def test_timeseries_periodindex(self):
|
||
# GH2891
|
||
from pandas import period_range
|
||
|
||
prng = period_range("1/1/2011", "1/1/2012", freq="M")
|
||
ts = Series(np.random.randn(len(prng)), prng)
|
||
new_ts = tm.round_trip_pickle(ts)
|
||
assert new_ts.index.freq == "M"
|
||
|
||
def test_pickle_preserve_name(self):
|
||
for n in [777, 777.0, "name", datetime(2001, 11, 11), (1, 2)]:
|
||
unpickled = self._pickle_roundtrip_name(tm.makeTimeSeries(name=n))
|
||
assert unpickled.name == n
|
||
|
||
def _pickle_roundtrip_name(self, obj):
|
||
|
||
with tm.ensure_clean() as path:
|
||
obj.to_pickle(path)
|
||
unpickled = pd.read_pickle(path)
|
||
return unpickled
|
||
|
||
def test_to_frame_expanddim(self):
|
||
# GH 9762
|
||
|
||
class SubclassedSeries(Series):
|
||
@property
|
||
def _constructor_expanddim(self):
|
||
return SubclassedFrame
|
||
|
||
class SubclassedFrame(DataFrame):
|
||
pass
|
||
|
||
s = SubclassedSeries([1, 2, 3], name="X")
|
||
result = s.to_frame()
|
||
assert isinstance(result, SubclassedFrame)
|
||
expected = SubclassedFrame({"X": [1, 2, 3]})
|
||
tm.assert_frame_equal(result, expected)
|