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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)