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test_io.py
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# coding=utf-8
# pylint: disable-msg=E1101,W0612
from datetime import datetime
import collections
import pytest
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from pandas.compat import StringIO, u
from pandas.util.testing import (assert_series_equal, assert_almost_equal,
assert_frame_equal, ensure_clean)
import pandas.util.testing as tm
from .common import TestData
class TestSeriesToCSV(TestData):
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_deprecation(self):
# see gh-17812
with ensure_clean() as path:
self.ts.to_csv(path)
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
ts = self.read_csv(path)
depr_ts = Series.from_csv(path)
assert_series_equal(depr_ts, ts)
def test_from_csv(self):
with ensure_clean() as path:
self.ts.to_csv(path)
ts = self.read_csv(path)
assert_series_equal(self.ts, ts, check_names=False)
assert ts.name is None
assert ts.index.name is None
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
depr_ts = Series.from_csv(path)
assert_series_equal(depr_ts, ts)
# see gh-10483
self.ts.to_csv(path, header=True)
ts_h = self.read_csv(path, header=0)
assert ts_h.name == "ts"
self.series.to_csv(path)
series = self.read_csv(path)
assert_series_equal(self.series, series, check_names=False)
assert series.name is None
assert series.index.name is None
self.series.to_csv(path, header=True)
series_h = self.read_csv(path, header=0)
assert series_h.name == "series"
outfile = open(path, "w")
outfile.write("1998-01-01|1.0\n1999-01-01|2.0")
outfile.close()
series = self.read_csv(path, sep="|")
check_series = Series({datetime(1998, 1, 1): 1.0,
datetime(1999, 1, 1): 2.0})
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})
assert_series_equal(check_series, series)
def test_to_csv(self):
import io
with ensure_clean() as path:
self.ts.to_csv(path)
with io.open(path, newline=None) as f:
lines = f.readlines()
assert (lines[1] != '\n')
self.ts.to_csv(path, index=False)
arr = np.loadtxt(path)
assert_almost_equal(arr, self.ts.values)
def test_to_csv_unicode_index(self):
buf = StringIO()
s = Series([u("\u05d0"), "d2"], index=[u("\u05d0"), u("\u05d1")])
s.to_csv(buf, encoding="UTF-8")
buf.seek(0)
s2 = self.read_csv(buf, index_col=0, encoding="UTF-8")
assert_series_equal(s, s2)
def test_to_csv_float_format(self):
with ensure_clean() as filename:
ser = Series([0.123456, 0.234567, 0.567567])
ser.to_csv(filename, float_format="%.2f")
rs = self.read_csv(filename)
xp = Series([0.12, 0.23, 0.57])
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)
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=None)
assert isinstance(csv_str, str)
def test_to_csv_compression(self, compression):
s = Series([0.123456, 0.234567, 0.567567], index=['A', 'B', 'C'],
name='X')
with ensure_clean() as filename:
s.to_csv(filename, compression=compression, header=True)
# test the round trip - to_csv -> read_csv
rs = pd.read_csv(filename, compression=compression,
index_col=0, squeeze=True)
assert_series_equal(s, rs)
# explicitly ensure file was compressed
with tm.decompress_file(filename, compression) as fh:
text = fh.read().decode('utf8')
assert s.name in text
with tm.decompress_file(filename, compression) as fh:
assert_series_equal(s, pd.read_csv(fh,
index_col=0,
squeeze=True))
class TestSeriesIO(TestData):
def test_to_frame(self):
self.ts.name = None
rs = self.ts.to_frame()
xp = pd.DataFrame(self.ts.values, index=self.ts.index)
assert_frame_equal(rs, xp)
self.ts.name = 'testname'
rs = self.ts.to_frame()
xp = pd.DataFrame(dict(testname=self.ts.values), index=self.ts.index)
assert_frame_equal(rs, xp)
rs = self.ts.to_frame(name='testdifferent')
xp = pd.DataFrame(
dict(testdifferent=self.ts.values), index=self.ts.index)
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., '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 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]})
assert_frame_equal(result, expected)
@pytest.mark.parametrize('mapping', (
dict,
collections.defaultdict(list),
collections.OrderedDict))
def test_to_dict(self, mapping):
# GH16122
ts = TestData().ts
tm.assert_series_equal(
Series(ts.to_dict(mapping), name='ts'), ts)
from_method = Series(ts.to_dict(collections.Counter))
from_constructor = Series(collections.Counter(ts.iteritems()))
tm.assert_series_equal(from_method, from_constructor)