def test_read_zipped_json():
uncompressed_path = tm.get_data_path("tsframe_v012.json")
uncompressed_df = pd.read_json(uncompressed_path)
compressed_path = tm.get_data_path("tsframe_v012.json.zip")
compressed_df = pd.read_json(compressed_path, compression='zip')
assert_frame_equal(uncompressed_df, compressed_df)
def test_parse_public_s3_bucket(self):
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
df = read_csv('s3://pandas-test/tips.csv' +
ext, compression=comp)
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
tm.assert_frame_equal(read_csv(
tm.get_data_path('tips.csv')), df)
# Read public file from bucket with not-public contents
df = read_csv('s3://cant_get_it/tips.csv')
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
tm.assert_frame_equal(read_csv(tm.get_data_path('tips.csv')), df)
def test_categorical_dtype_encoding(self):
# GH 10153
pth = tm.get_data_path("unicode_series.csv")
encoding = "latin-1"
expected = self.read_csv(pth, header=None, encoding=encoding)
expected[1] = Categorical(expected[1])
actual = self.read_csv(pth, header=None, encoding=encoding, dtype={1: "category"})
tm.assert_frame_equal(actual, expected)
pth = tm.get_data_path("utf16_ex.txt")
encoding = "utf-16"
expected = self.read_table(pth, encoding=encoding)
expected = expected.apply(Categorical)
actual = self.read_table(pth, encoding=encoding, dtype="category")
tm.assert_frame_equal(actual, expected)
def test_parse_public_s3a_bucket(self):
# Read from AWS s3 as "s3a" URL
df = read_csv('s3a://pandas-test/tips.csv', nrows=10)
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
tm.assert_frame_equal(read_csv(
tm.get_data_path('tips.csv')).iloc[:10], df)
def test_pickles(current_pickle_data, version, f):
if not is_platform_little_endian():
pytest.skip("known failure on non-little endian")
vf = tm.get_data_path('legacy_pickle/{}/{}'.format(version, f))
with catch_warnings(record=True):
compare(current_pickle_data, vf, version)
def setUp(self):
if sys.version_info < (2, 7, 0):
import nose
raise nose.SkipTest("Doesn't support Python 2.6 because of ElementTree incompat")
self.dirpath = tm.get_data_path()
def test_parse_public_s3n_bucket(self):
# Read from AWS s3 as "s3n" URL
df = read_csv('s3n://pandas-test/tips.csv', nrows=10)
assert isinstance(df, DataFrame)
assert not df.empty
tm.assert_frame_equal(read_csv(
tm.get_data_path('tips.csv')).iloc[:10], df)
def legacy_packers_versions():
# yield the packers versions
path = tm.get_data_path('legacy_msgpack')
for v in os.listdir(path):
p = os.path.join(path, v)
if os.path.isdir(p):
yield v
def legacy_pickle_versions():
# yield the pickle versions
path = tm.get_data_path('legacy_pickle')
for v in os.listdir(path):
p = os.path.join(path, v)
if os.path.isdir(p):
yield v
def test_categorical_dtype_encoding(self):
# GH 10153
pth = tm.get_data_path('unicode_series.csv')
encoding = 'latin-1'
expected = self.read_csv(pth, header=None, encoding=encoding)
expected[1] = Categorical(expected[1])
actual = self.read_csv(pth, header=None, encoding=encoding,
dtype={1: 'category'})
tm.assert_frame_equal(actual, expected)
pth = tm.get_data_path('utf16_ex.txt')
encoding = 'utf-16'
expected = self.read_table(pth, encoding=encoding)
expected = expected.apply(Categorical)
actual = self.read_table(pth, encoding=encoding, dtype='category')
tm.assert_frame_equal(actual, expected)
def test_parse_public_s3_bucket_chunked(self):
# Read with a chunksize
chunksize = 5
local_tips = read_csv(tm.get_data_path('tips.csv'))
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
if comp == 'bz2' and compat.PY2:
# The Python 2 C parser can't read bz2 from S3.
self.assertRaises(ValueError, read_csv,
's3://pandas-test/tips.csv' + ext,
compression=comp)
else:
df_reader = read_csv('s3://pandas-test/tips.csv' + ext,
chunksize=chunksize, compression=comp)
self.assertEqual(df_reader.chunksize, chunksize)
for i_chunk in [0, 1, 2]:
# Read a couple of chunks and make sure we see them
# properly.
df = df_reader.get_chunk()
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
true_df = local_tips.iloc[
chunksize * i_chunk: chunksize * (i_chunk + 1)]
# Chunking doesn't preserve row numbering
true_df = true_df.reset_index().drop('index', axis=1)
tm.assert_frame_equal(true_df, df)
def test_12659():
dirpath = tm.get_data_path()
fname = os.path.join(dirpath, "test_12659.sas7bdat")
df = pd.read_sas(fname)
fname = os.path.join(dirpath, "test_12659.csv")
df0 = pd.read_csv(fname)
df0 = df0.astype(np.float64)
tm.assert_frame_equal(df, df0)
def test_read_pickles_0_11_0(self):
if not is_little_endian():
raise nose.SkipTest("known failure of test_read_pickles_0_11_0 on non-little endian")
pth = tm.get_data_path('legacy_pickle/0.11.0')
for f in os.listdir(pth):
vf = os.path.join(pth,f)
self.compare(vf)
def test_parse_public_s3_bucket_nrows_python(self):
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
df = read_csv('s3://pandas-test/tips.csv' + ext, engine='python',
nrows=10, compression=comp)
assert isinstance(df, DataFrame)
assert not df.empty
tm.assert_frame_equal(read_csv(
tm.get_data_path('tips.csv')).iloc[:10], df)
def read_pickles(self, version):
if not is_little_endian():
raise nose.SkipTest("known failure on non-little endian")
pth = tm.get_data_path('legacy_pickle/{0}'.format(str(version)))
for f in os.listdir(pth):
vf = os.path.join(pth,f)
self.compare(vf)
def test_url(self):
# HTTP(S)
url = "https://raw.github.com/pydata/pandas/master/" "pandas/io/tests/parser/data/salary.table.csv"
url_table = self.read_table(url)
dirpath = tm.get_data_path()
localtable = os.path.join(dirpath, "salary.table.csv")
local_table = self.read_table(localtable)
tm.assert_frame_equal(url_table, local_table)
def test_airline():
dirpath = tm.get_data_path()
fname = os.path.join(dirpath, "airline.sas7bdat")
df = pd.read_sas(fname)
fname = os.path.join(dirpath, "airline.csv")
df0 = pd.read_csv(fname)
df0 = df0.astype(np.float64)
tm.assert_frame_equal(df, df0, check_exact=False)
def test_parse_public_s3_bucket_nrows(self):
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
df = read_csv('s3://pandas-test/tips.csv' +
ext, nrows=10, compression=comp)
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
tm.assert_frame_equal(read_csv(
tm.get_data_path('tips.csv')).iloc[:10], df)
def test_infer_s3_compression(self):
for ext in ['', '.gz', '.bz2']:
df = read_csv('s3://pandas-test/tips.csv' + ext,
engine='python', compression='infer')
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
tm.assert_frame_equal(read_csv(
tm.get_data_path('tips.csv')), df)
def test_infer_s3_compression(self, s3_resource):
for ext in ['', '.gz', '.bz2']:
df = read_csv('s3://pandas-test/tips.csv' + ext,
engine='python', compression='infer')
assert isinstance(df, DataFrame)
assert not df.empty
tm.assert_frame_equal(read_csv(
tm.get_data_path('tips.csv')), df)
def test_parse_public_s3_bucket(self):
pytest.importorskip('s3fs')
# more of an integration test due to the not-public contents portion
# can probably mock this though.
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
df = read_csv('s3://pandas-test/tips.csv' +
ext, compression=comp)
assert isinstance(df, DataFrame)
assert not df.empty
tm.assert_frame_equal(read_csv(
tm.get_data_path('tips.csv')), df)
# Read public file from bucket with not-public contents
df = read_csv('s3://cant_get_it/tips.csv')
assert isinstance(df, DataFrame)
assert not df.empty
tm.assert_frame_equal(read_csv(tm.get_data_path('tips.csv')), df)
def test_date_time():
# Support of different SAS date/datetime formats (PR #15871)
dirpath = tm.get_data_path()
fname = os.path.join(dirpath, "datetime.sas7bdat")
df = pd.read_sas(fname)
fname = os.path.join(dirpath, "datetime.csv")
df0 = pd.read_csv(fname, parse_dates=['Date1', 'Date2', 'DateTime',
'DateTimeHi', 'Taiw'])
tm.assert_frame_equal(df, df0)
def test_msgpack(self):
msgpack_path = tm.get_data_path('legacy_msgpack')
n = 0
for v in os.listdir(msgpack_path):
pth = os.path.join(msgpack_path, v)
if os.path.isdir(pth):
yield self.read_msgpacks, v
n += 1
assert n > 0, 'Msgpack files are not tested'
def read_msgpacks(self, version):
pth = tm.get_data_path('legacy_msgpack/{0}'.format(str(version)))
n = 0
for f in os.listdir(pth):
vf = os.path.join(pth, f)
self.compare(vf, version)
n += 1
assert n > 0, 'Msgpack files are not tested'
def test_productsales():
dirpath = tm.get_data_path()
fname = os.path.join(dirpath, "productsales.sas7bdat")
df = pd.read_sas(fname, encoding='utf-8')
fname = os.path.join(dirpath, "productsales.csv")
df0 = pd.read_csv(fname, parse_dates=['MONTH'])
vn = ["ACTUAL", "PREDICT", "QUARTER", "YEAR"]
df0[vn] = df0[vn].astype(np.float64)
tm.assert_frame_equal(df, df0)
def setUp(self):
self.dirpath = tm.get_data_path()
self.csv1 = os.path.join(self.dirpath, "test1.csv")
self.csv2 = os.path.join(self.dirpath, "test2.csv")
self.xls1 = os.path.join(self.dirpath, "test.xls")
self.frame = _frame.copy()
self.frame2 = _frame2.copy()
self.tsframe = _tsframe.copy()
self.mixed_frame = _mixed_frame.copy()
def test_pickles(self):
pickle_path = tm.get_data_path('legacy_pickle')
n = 0
for v in os.listdir(pickle_path):
pth = os.path.join(pickle_path, v)
if os.path.isdir(pth):
yield self.read_pickles, v
n += 1
assert n > 0, 'Pickle files are not tested'
def read_data(self, name, dedupe=False):
path = os.path.join(tm.get_data_path(), name)
x = read_csv(path)
if dedupe:
x = (x.drop_duplicates(['time', 'ticker'], keep='last')
.reset_index(drop=True)
)
x.time = to_datetime(x.time)
return x
def setUp(self):
# Unit test datasets for dta7 - dta9 (old stata formats 104, 105 and 107) can be downloaded from:
# http://stata-press.com/data/glmext.html
self.dirpath = tm.get_data_path()
self.dta1_114 = os.path.join(self.dirpath, 'stata1_114.dta')
self.dta1_117 = os.path.join(self.dirpath, 'stata1_117.dta')
self.dta2_113 = os.path.join(self.dirpath, 'stata2_113.dta')
self.dta2_114 = os.path.join(self.dirpath, 'stata2_114.dta')
self.dta2_115 = os.path.join(self.dirpath, 'stata2_115.dta')
self.dta2_117 = os.path.join(self.dirpath, 'stata2_117.dta')
self.dta3_113 = os.path.join(self.dirpath, 'stata3_113.dta')
self.dta3_114 = os.path.join(self.dirpath, 'stata3_114.dta')
self.dta3_115 = os.path.join(self.dirpath, 'stata3_115.dta')
self.dta3_117 = os.path.join(self.dirpath, 'stata3_117.dta')
self.csv3 = os.path.join(self.dirpath, 'stata3.csv')
self.dta4_113 = os.path.join(self.dirpath, 'stata4_113.dta')
self.dta4_114 = os.path.join(self.dirpath, 'stata4_114.dta')
self.dta4_115 = os.path.join(self.dirpath, 'stata4_115.dta')
self.dta4_117 = os.path.join(self.dirpath, 'stata4_117.dta')
self.dta7 = os.path.join(self.dirpath, 'cancer.dta')
self.csv7 = os.path.join(self.dirpath, 'cancer.csv')
self.dta8 = os.path.join(self.dirpath, 'tbl19-3.dta')
self.csv8 = os.path.join(self.dirpath, 'tbl19-3.csv')
self.dta9 = os.path.join(self.dirpath, 'lbw.dta')
self.csv9 = os.path.join(self.dirpath, 'lbw.csv')
self.dta_encoding = os.path.join(self.dirpath, 'stata1_encoding.dta')
self.csv14 = os.path.join(self.dirpath, 'stata5.csv')
self.dta14_113 = os.path.join(self.dirpath, 'stata5_113.dta')
self.dta14_114 = os.path.join(self.dirpath, 'stata5_114.dta')
self.dta14_115 = os.path.join(self.dirpath, 'stata5_115.dta')
self.dta14_117 = os.path.join(self.dirpath, 'stata5_117.dta')
self.csv15 = os.path.join(self.dirpath, 'stata6.csv')
self.dta15_113 = os.path.join(self.dirpath, 'stata6_113.dta')
self.dta15_114 = os.path.join(self.dirpath, 'stata6_114.dta')
self.dta15_115 = os.path.join(self.dirpath, 'stata6_115.dta')
self.dta15_117 = os.path.join(self.dirpath, 'stata6_117.dta')
self.dta16_115 = os.path.join(self.dirpath, 'stata7_115.dta')
self.dta16_117 = os.path.join(self.dirpath, 'stata7_117.dta')
self.dta17_113 = os.path.join(self.dirpath, 'stata8_113.dta')
self.dta17_115 = os.path.join(self.dirpath, 'stata8_115.dta')
self.dta17_117 = os.path.join(self.dirpath, 'stata8_117.dta')
self.dta18_115 = os.path.join(self.dirpath, 'stata9_115.dta')
self.dta18_117 = os.path.join(self.dirpath, 'stata9_117.dta')
def test_read_from_http_url(self):
_skip_if_no_xlrd()
url = ('https://raw.github.com/pydata/pandas/master/'
'pandas/io/tests/data/test.xlsx')
url_table = read_excel(url)
dirpath = tm.get_data_path()
localtable = os.path.join(dirpath, 'test.xlsx')
local_table = read_excel(localtable)
tm.assert_frame_equal(url_table, local_table)
def test_pickles(current_pickle_data, version):
if not is_platform_little_endian():
pytest.skip("known failure on non-little endian")
pth = tm.get_data_path('legacy_pickle/{0}'.format(version))
n = 0
for f in os.listdir(pth):
vf = os.path.join(pth, f)
data = compare(current_pickle_data, vf, version)
if data is None:
continue
n += 1
assert n > 0, 'Pickle files are not tested'
def read_pickles(self, version):
if not is_platform_little_endian():
raise nose.SkipTest("known failure on non-little endian")
pth = tm.get_data_path('legacy_pickle/{0}'.format(str(version)))
n = 0
for f in os.listdir(pth):
vf = os.path.join(pth, f)
data = self.compare(vf, version)
if data is None:
continue
n += 1
assert n > 0, 'Pickle files are not tested'
def setUp(self):
# Unit test datasets for dta7 - dta9 (old stata formats 104, 105 and 107) can be downloaded from:
# http://stata-press.com/data/glmext.html
self.dirpath = tm.get_data_path()
self.dta1_114 = os.path.join(self.dirpath, 'stata1_114.dta')
self.dta1_117 = os.path.join(self.dirpath, 'stata1_117.dta')
self.dta2_113 = os.path.join(self.dirpath, 'stata2_113.dta')
self.dta2_114 = os.path.join(self.dirpath, 'stata2_114.dta')
self.dta2_115 = os.path.join(self.dirpath, 'stata2_115.dta')
self.dta2_117 = os.path.join(self.dirpath, 'stata2_117.dta')
self.dta3_113 = os.path.join(self.dirpath, 'stata3_113.dta')
self.dta3_114 = os.path.join(self.dirpath, 'stata3_114.dta')
self.dta3_115 = os.path.join(self.dirpath, 'stata3_115.dta')
self.dta3_117 = os.path.join(self.dirpath, 'stata3_117.dta')
self.csv3 = os.path.join(self.dirpath, 'stata3.csv')
self.dta4_113 = os.path.join(self.dirpath, 'stata4_113.dta')
self.dta4_114 = os.path.join(self.dirpath, 'stata4_114.dta')
self.dta4_115 = os.path.join(self.dirpath, 'stata4_115.dta')
self.dta4_117 = os.path.join(self.dirpath, 'stata4_117.dta')
self.dta7 = os.path.join(self.dirpath, 'cancer.dta')
self.csv7 = os.path.join(self.dirpath, 'cancer.csv')
self.dta8 = os.path.join(self.dirpath, 'tbl19-3.dta')
self.csv8 = os.path.join(self.dirpath, 'tbl19-3.csv')
self.dta9 = os.path.join(self.dirpath, 'lbw.dta')
self.csv9 = os.path.join(self.dirpath, 'lbw.csv')
self.dta_encoding = os.path.join(self.dirpath, 'stata1_encoding.dta')
self.csv14 = os.path.join(self.dirpath, 'stata5.csv')
self.dta14_113 = os.path.join(self.dirpath, 'stata5_113.dta')
self.dta14_114 = os.path.join(self.dirpath, 'stata5_114.dta')
self.dta14_115 = os.path.join(self.dirpath, 'stata5_115.dta')
self.dta14_117 = os.path.join(self.dirpath, 'stata5_117.dta')
self.csv15 = os.path.join(self.dirpath, 'stata6.csv')
self.dta15_113 = os.path.join(self.dirpath, 'stata6_113.dta')
self.dta15_114 = os.path.join(self.dirpath, 'stata6_114.dta')
self.dta15_115 = os.path.join(self.dirpath, 'stata6_115.dta')
self.dta15_117 = os.path.join(self.dirpath, 'stata6_117.dta')
self.dta16_115 = os.path.join(self.dirpath, 'stata7_115.dta')
self.dta16_117 = os.path.join(self.dirpath, 'stata7_117.dta')
def setUpClass(self):
# Integration tests require a valid bigquery token
# be present in the user's home directory. This
# can be generated with 'bq init' in the command line
self.dirpath = tm.get_data_path()
home = os.path.expanduser("~")
self.bq_token = os.path.join(home, '.bigquery.v2.token')
self.fake_job_path = os.path.join(self.dirpath, 'gbq_fake_job.txt')
# If we're using a valid token, make a test dataset
# Note, dataset functionality is beyond the scope
# of the module under test, so we rely on the command
# line utility for this.
if os.path.exists(self.bq_token):
subprocess.call(['bq', 'mk', '-d', 'pandas_testing_dataset'])
def test_pickle_v0_15_2():
# ordered -> _ordered
# GH 9347
cat = pd.Categorical(values=['a', 'b', 'c'], ordered=False,
categories=['a', 'b', 'c', 'd'])
pickle_path = os.path.join(tm.get_data_path(),
'categorical_0_15_2.pickle')
# This code was executed once on v0.15.2 to generate the pickle:
#
# cat = Categorical(labels=np.arange(3), levels=['a', 'b', 'c', 'd'],
# name='foobar')
# with open(pickle_path, 'wb') as f: pickle.dump(cat, f)
#
tm.assert_categorical_equal(cat, pd.read_pickle(pickle_path))
def setUp(self):
# Unit test datasets for dta7 - dta9 (old stata formats 104, 105 and 107) can be downloaded from:
# http://stata-press.com/data/glmext.html
self.dirpath = tm.get_data_path()
self.dta1 = os.path.join(self.dirpath, 'stata1.dta')
self.dta2 = os.path.join(self.dirpath, 'stata2.dta')
self.dta3 = os.path.join(self.dirpath, 'stata3.dta')
self.csv3 = os.path.join(self.dirpath, 'stata3.csv')
self.dta4 = os.path.join(self.dirpath, 'stata4.dta')
self.dta7 = os.path.join(self.dirpath, 'cancer.dta')
self.csv7 = os.path.join(self.dirpath, 'cancer.csv')
self.dta8 = os.path.join(self.dirpath, 'tbl19-3.dta')
self.csv8 = os.path.join(self.dirpath, 'tbl19-3.csv')
self.dta9 = os.path.join(self.dirpath, 'lbw.dta')
self.csv9 = os.path.join(self.dirpath, 'lbw.csv')
def read_pickles(self, version):
if not is_little_endian():
raise nose.SkipTest("known failure on non-little endian")
pth = tm.get_data_path('legacy_pickle/{0}'.format(str(version)))
for f in os.listdir(pth):
vf = os.path.join(pth,f)
data = self.compare(vf)
if data is None:
continue
if 'series' in data:
if 'ts' in data['series']:
self._validate_timeseries(data['series']['ts'], self.data['series']['ts'])
def setUpClass(cls):
super(TestYahooOptions, cls).setUpClass()
# aapl has monthlies
cls.aapl = web.Options('aapl', 'yahoo')
today = datetime.today()
cls.year = today.year
cls.month = today.month + 1
if cls.month > 12: # pragma: no cover
cls.month = 1
cls.year = cls.year + 1
cls.expiry = datetime(cls.year, cls.month, 1)
cls.dirpath = tm.get_data_path()
cls.json1 = 'file://' + os.path.join(cls.dirpath, 'yahoo_options1.json')
cls.json2 = 'file://' + os.path.join(cls.dirpath, 'yahoo_options2.json') # Empty table GH#22
cls.data1 = cls.aapl._process_data(cls.aapl._parse_url(cls.json1))
def test_parse_public_s3_bucket_nrows(self):
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
if comp == 'bz2' and compat.PY2:
# The Python 2 C parser can't read bz2 from S3.
self.assertRaises(ValueError,
read_csv,
's3://pandas-test/tips.csv' + ext,
compression=comp)
else:
df = read_csv('s3://pandas-test/tips.csv' + ext,
nrows=10,
compression=comp)
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
tm.assert_frame_equal(
read_csv(tm.get_data_path('tips.csv')).iloc[:10], df)
def test_file(self):
# FILE
if sys.version_info[:2] < (2, 6):
raise nose.SkipTest("file:// not supported with Python < 2.6")
dirpath = tm.get_data_path()
localtable = os.path.join(dirpath, 'salary.table.csv')
local_table = self.read_table(localtable)
try:
url_table = self.read_table('file://localhost/' + localtable)
except URLError:
# fails on some systems
raise nose.SkipTest("failing on %s" %
' '.join(platform.uname()).strip())
tm.assert_frame_equal(url_table, local_table)
def boto3_client_s3(self):
# see gh-16135
# boto3 is a dependency of s3fs
import boto3
client = boto3.client("s3")
key = "/tips.csv"
bucket = "pandas-test"
s3_object = client.get_object(Bucket=bucket, Key=key)
result = read_csv(s3_object["Body"])
assert isinstance(result, DataFrame)
assert not result.empty
expected = read_csv(tm.get_data_path('tips.csv'))
tm.assert_frame_equal(result, expected)
def test_pickle_v0_14_1():
# we have the name warning
# 10482
with tm.assert_produces_warning(UserWarning):
cat = pd.Categorical(values=['a', 'b', 'c'],
categories=['a', 'b', 'c', 'd'],
name='foobar',
ordered=False)
pickle_path = os.path.join(tm.get_data_path(), 'categorical_0_14_1.pickle')
# This code was executed once on v0.14.1 to generate the pickle:
#
# cat = Categorical(labels=np.arange(3), levels=['a', 'b', 'c', 'd'],
# name='foobar')
# with open(pickle_path, 'wb') as f: pickle.dump(cat, f)
#
tm.assert_categorical_equal(cat, pd.read_pickle(pickle_path))
def test_encoding_options():
dirpath = tm.get_data_path()
fname = os.path.join(dirpath, "test1.sas7bdat")
df1 = pd.read_sas(fname)
df2 = pd.read_sas(fname, encoding='utf-8')
for col in df1.columns:
try:
df1[col] = df1[col].str.decode('utf-8')
except AttributeError:
pass
tm.assert_frame_equal(df1, df2)
from pandas.io.sas.sas7bdat import SAS7BDATReader
rdr = SAS7BDATReader(fname, convert_header_text=False)
df3 = rdr.read()
for x, y in zip(df1.columns, df3.columns):
assert(x == y.decode())
def test_parse_public_s3_bucket_chunked_python(self):
# Read with a chunksize using the Python parser
chunksize = 5
local_tips = read_csv(tm.get_data_path('tips.csv'))
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
df_reader = read_csv('s3://pandas-test/tips.csv' + ext,
chunksize=chunksize, compression=comp,
engine='python')
self.assertEqual(df_reader.chunksize, chunksize)
for i_chunk in [0, 1, 2]:
# Read a couple of chunks and make sure we see them properly.
df = df_reader.get_chunk()
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
true_df = local_tips.iloc[
chunksize * i_chunk: chunksize * (i_chunk + 1)]
tm.assert_frame_equal(true_df, df)
def test_parse_public_s3_bucket_chunked(self):
# Read with a chunksize
chunksize = 5
local_tips = read_csv(tm.get_data_path('tips.csv'))
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
df_reader = read_csv('s3://pandas-test/tips.csv' + ext,
chunksize=chunksize, compression=comp)
assert df_reader.chunksize == chunksize
for i_chunk in [0, 1, 2]:
# Read a couple of chunks and make sure we see them
# properly.
df = df_reader.get_chunk()
assert isinstance(df, DataFrame)
assert not df.empty
true_df = local_tips.iloc[
chunksize * i_chunk: chunksize * (i_chunk + 1)]
tm.assert_frame_equal(true_df, df)
def read_msgpacks(self, version):
pth = tm.get_data_path('legacy_msgpack/{0}'.format(str(version)))
n = 0
for f in os.listdir(pth):
# GH12142 0.17 files packed in P2 can't be read in P3
if (compat.PY3 and version.startswith('0.17.')
and f.split('.')[-4][-1] == '2'):
continue
vf = os.path.join(pth, f)
try:
self.compare(vf, version)
except ImportError:
# blosc not installed
continue
n += 1
assert n > 0, 'Msgpack files are not tested'
def setUpClass(cls):
super(TestYahooOptions, cls).setUpClass()
_skip_if_no_lxml()
# aapl has monthlies
cls.aapl = web.Options('aapl', 'yahoo')
today = datetime.today()
cls.year = today.year
cls.month = today.month + 1
if cls.month > 12:
cls.year = cls.year + 1
cls.month = 1
cls.expiry = datetime(cls.year, cls.month, 1)
cls.dirpath = tm.get_data_path()
cls.html1 = os.path.join(cls.dirpath, 'yahoo_options1.html')
cls.html2 = os.path.join(cls.dirpath, 'yahoo_options2.html')
cls.data1 = cls.aapl._option_frames_from_url(cls.html1)['puts']
def setUpClass(cls):
super(TestYahooOptions, cls).setUpClass()
_skip_if_no_lxml()
# aapl has monthlies
cls.aapl = web.Options('aapl', 'yahoo')
d = (Timestamp.today() + pd.offsets.MonthBegin(1)).normalize()
cls.year = d.year
cls.month = d.month
cls.expiry = d
cls.expiry2 = d + pd.offsets.MonthBegin(1)
cls.dirpath = tm.get_data_path()
cls.html1 = os.path.join(cls.dirpath, 'yahoo_options1.html')
cls.html2 = os.path.join(cls.dirpath, 'yahoo_options2.html')
cls.html3 = os.path.join(cls.dirpath,
'yahoo_options3.html') #Empty table GH#22
cls.data1 = cls.aapl._option_frames_from_url(cls.html1)['puts']
def setUpClass(cls):
super(TestYahooOptions, cls).setUpClass()
_skip_if_no_lxml()
# aapl has monthlies
cls.aapl = web.Options('aapl', 'yahoo')
today = datetime.today()
year = today.year
month = today.month + 1
if month > 12:
year = year + 1
month = 1
cls.expiry = datetime(year, month, 1)
cls.dirpath = tm.get_data_path()
cls.html1 = os.path.join(cls.dirpath, 'yahoo_options1.html')
cls.html2 = os.path.join(cls.dirpath, 'yahoo_options2.html')
cls.root1 = cls.aapl._parse_url(cls.html1)
cls.root2 = cls.aapl._parse_url(cls.html2)
def test_read_from_file_url(self):
_skip_if_no_xlrd()
# FILE
if sys.version_info[:2] < (2, 6):
raise nose.SkipTest("file:// not supported with Python < 2.6")
dirpath = tm.get_data_path()
localtable = os.path.join(dirpath, 'test.xlsx')
local_table = read_excel(localtable)
try:
url_table = read_excel('file://localhost/' + localtable)
except URLError:
# fails on some systems
raise nose.SkipTest("failing on %s" %
' '.join(platform.uname()).strip())
tm.assert_frame_equal(url_table, local_table)
def test_msgpacks_legacy(self, current_packers_data, all_packers_data,
version):
pth = tm.get_data_path("legacy_msgpack/{0}".format(version))
n = 0
for f in os.listdir(pth):
# GH12142 0.17 files packed in P2 can't be read in P3
if (compat.PY3 and version.startswith("0.17.")
and f.split(".")[-4][-1] == "2"):
continue
vf = os.path.join(pth, f)
try:
self.compare(current_packers_data, all_packers_data, vf,
version)
except ImportError:
# blosc not installed
continue
n += 1
assert n > 0, "Msgpack files are not tested"
def test_msgpacks_legacy(self, current_packers_data, all_packers_data,
version):
pth = tm.get_data_path('legacy_msgpack/{0}'.format(version))
n = 0
for f in os.listdir(pth):
# GH12142 0.17 files packed in P2 can't be read in P3
if (compat.PY3 and version.startswith('0.17.')
and f.split('.')[-4][-1] == '2'):
continue
vf = os.path.join(pth, f)
try:
with catch_warnings(record=True):
self.compare(current_packers_data, all_packers_data, vf,
version)
except ImportError:
# blosc not installed
continue
n += 1
assert n > 0, 'Msgpack files are not tested'
def setup_class(cls):
# AAPL has monthlies
cls.aapl = web.Options('aapl', 'yahoo')
today = datetime.today()
cls.year = today.year
cls.month = today.month + 1
if cls.month > 12: # pragma: no cover
cls.month = 1
cls.year = cls.year + 1
cls.expiry = datetime(cls.year, cls.month, 1)
cls.dirpath = tm.get_data_path()
cls.json1 = 'file://' + os.path.join(
cls.dirpath, 'yahoo_options1.json')
# see gh-22: empty table
cls.json2 = 'file://' + os.path.join(
cls.dirpath, 'yahoo_options2.json')
cls.data1 = cls.aapl._process_data(cls.aapl._parse_url(cls.json1))
def setUp(self):
self.dirpath = tm.get_data_path()
self.ts = tm.makeTimeSeries()
self.ts.name = 'ts'
self.series = tm.makeStringSeries()
self.series.name = 'series'
self.objSeries = tm.makeObjectSeries()
self.objSeries.name = 'objects'
self.empty_series = Series([], index=[])
self.empty_frame = DataFrame({})
self.frame = _frame.copy()
self.frame2 = _frame2.copy()
self.intframe = _intframe.copy()
self.tsframe = _tsframe.copy()
self.mixed_frame = _mixed_frame.copy()
def test_qcut_binning_issues(self):
# #1978, 1979
path = os.path.join(tm.get_data_path(), 'cut_data.csv')
arr = np.loadtxt(path)
result = qcut(arr, 20)
starts = []
ends = []
for lev in result.categories:
s, e = lev[1:-1].split(',')
self.assertTrue(s != e)
starts.append(float(s))
ends.append(float(e))
for (sp, sn), (ep, en) in zip(zip(starts[:-1], starts[1:]),
zip(ends[:-1], ends[1:])):
self.assertTrue(sp < sn)
self.assertTrue(ep < en)
self.assertTrue(ep <= sn)
def setUpClass(cls):
super(TestYahooOptions, cls).setUpClass()
_skip_if_no_lxml()
# aapl has monthlies
cls.aapl = web.Options('aapl', 'yahoo')
today = datetime.today()
year = today.year
month = today.month + 1
if month > 12:
year = year + 1
month = 1
cls.expiry = datetime(year, month, 1)
cls.dirpath = tm.get_data_path()
cls.html1 = os.path.join(cls.dirpath, 'yahoo_options1.html')
cls.html2 = os.path.join(cls.dirpath, 'yahoo_options2.html')
cls.root1 = cls.aapl._parse_url(cls.html1)
cls.root2 = cls.aapl._parse_url(cls.html2)
cls.tables1 = cls.aapl._parse_option_page_from_yahoo(cls.root1)
cls.unprocessed_data1 = web._parse_options_data(
cls.tables1[cls.aapl._TABLE_LOC['puts']])
cls.data1 = cls.aapl._process_data(cls.unprocessed_data1, 'put')
def test_qcut_binning_issues(self):
# #1978, 1979
path = os.path.join(tm.get_data_path(), 'cut_data.csv')
arr = np.loadtxt(path)
result = qcut(arr, 20)
starts = []
ends = []
for lev in np.unique(result):
s = lev.left
e = lev.right
assert s != e
starts.append(float(s))
ends.append(float(e))
for (sp, sn), (ep, en) in zip(zip(starts[:-1], starts[1:]),
zip(ends[:-1], ends[1:])):
assert sp < sn
assert ep < en
assert ep <= sn
def setUp(self):
self.dirpath = tm.get_data_path()
self.data = []
self.test_ix = [list(range(1, 16)), [16]]
for j in 1, 2:
fname = os.path.join(self.dirpath, "test_sas7bdat_%d.csv" % j)
df = pd.read_csv(fname)
epoch = pd.datetime(1960, 1, 1)
t1 = pd.to_timedelta(df["Column4"], unit='d')
df["Column4"] = epoch + t1
t2 = pd.to_timedelta(df["Column12"], unit='d')
df["Column12"] = epoch + t2
for k in range(df.shape[1]):
col = df.iloc[:, k]
if col.dtype == np.int64:
df.iloc[:, k] = df.iloc[:, k].astype(np.float64)
elif col.dtype == np.dtype('O'):
if PY2:
f = lambda x: (x.decode('utf-8')
if isinstance(x, str) else x)
df.iloc[:, k] = df.iloc[:, k].apply(f)
self.data.append(df)
def test_parse_public_s3_bucket_chunked(self):
# Read with a chunksize
chunksize = 5
local_tips = read_csv(tm.get_data_path('tips.csv'))
for ext, comp in [('', None), ('.gz', 'gzip'), ('.bz2', 'bz2')]:
if comp == 'bz2' and compat.PY2:
# The Python 2 C parser can't read bz2 from S3.
self.assertRaises(ValueError, read_csv,
's3://pandas-test/tips.csv' + ext,
compression=comp)
else:
df_reader = read_csv('s3://pandas-test/tips.csv' + ext,
chunksize=chunksize, compression=comp)
self.assertEqual(df_reader.chunksize, chunksize)
for i_chunk in [0, 1, 2]:
# Read a couple of chunks and make sure we see them
# properly.
df = df_reader.get_chunk()
self.assertTrue(isinstance(df, DataFrame))
self.assertFalse(df.empty)
true_df = local_tips.iloc[
chunksize * i_chunk: chunksize * (i_chunk + 1)]
tm.assert_frame_equal(true_df, df)
def read_pickles(self, version):
if not is_little_endian():
raise nose.SkipTest("known failure on non-little endian")
pth = tm.get_data_path('legacy_pickle/{0}'.format(str(version)))
n = 0
for f in os.listdir(pth):
vf = os.path.join(pth, f)
data = self.compare(vf)
if data is None:
continue
if 'series' in data:
if 'ts' in data['series']:
self._validate_timeseries(data['series']['ts'],
self.data['series']['ts'])
self._validate_frequency(data['series']['ts'])
if 'index' in data:
if 'period' in data['index']:
self._validate_periodindex(data['index']['period'],
self.data['index']['period'])
n += 1
assert n > 0, 'Pickle files are not tested'
