def _read_one_data(self, url, params):
resp_dsd = self._get_response(self.dsd_url)
dsd = _read_sdmx_dsd(resp_dsd.content)
resp = self._get_response(url)
data = read_sdmx(resp.content, dsd=dsd)
try:
data.index = pd.to_datetime(data.index)
data = data.sort_index()
data = data.truncate(self.start, self.end)
except ValueError:
pass
return data
def test_tourism(dirpath):
# Eurostat
# Employed doctorate holders in non managerial and non professional
# occupations by fields of science (%)
dsd = _read_sdmx_dsd(os.path.join(dirpath, "sdmx", "DSD_cdh_e_fos.xml"))
df = read_sdmx(os.path.join(dirpath, "sdmx", "cdh_e_fos.xml"), dsd=dsd)
assert isinstance(df, pd.DataFrame)
assert df.shape == (2, 336)
df = df["Percentage"]["Total"]["Natural sciences"]
df = df[["Norway", "Poland", "Portugal", "Russia"]]
exp_col = pd.MultiIndex.from_product(
[["Norway", "Poland", "Portugal", "Russia"], ["Annual"]], names=["GEO", "FREQ"]
)
exp_idx = pd.DatetimeIndex(["2009", "2006"], name="TIME_PERIOD")
values = np.array([[20.38, 25.1, 27.77, 38.1], [25.49, np.nan, 39.05, np.nan]])
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(df, expected)
def test_tourism(dirpath):
# Eurostat
# Employed doctorate holders in non managerial and non professional
# occupations by fields of science (%)
dsd = _read_sdmx_dsd(os.path.join(dirpath, 'sdmx', 'DSD_cdh_e_fos.xml'))
df = read_sdmx(os.path.join(dirpath, 'sdmx', 'cdh_e_fos.xml'), dsd=dsd)
assert isinstance(df, pd.DataFrame)
assert df.shape == (2, 336)
df = df['Percentage']['Total']['Natural sciences']
df = df[['Norway', 'Poland', 'Portugal', 'Russia']]
exp_col = pd.MultiIndex.from_product(
[['Norway', 'Poland', 'Portugal', 'Russia'], ['Annual']],
names=['GEO', 'FREQ'])
exp_idx = pd.DatetimeIndex(['2009', '2006'], name='TIME_PERIOD')
values = np.array([[20.38, 25.1, 27.77, 38.1],
[25.49, np.nan, 39.05, np.nan]])
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(df, expected)
def test_tourism(self):
# Eurostat
# Employed doctorate holders in non managerial and non professional
# occupations by fields of science (%)
dsd = _read_sdmx_dsd(os.path.join(self.dirpath, 'sdmx', 'DSD_cdh_e_fos.xml'))
df = read_sdmx(os.path.join(self.dirpath, 'sdmx', 'cdh_e_fos.xml'), dsd=dsd)
self.assertTrue(isinstance(df, pd.DataFrame))
self.assertEqual(df.shape, (2, 336))
df = df['Percentage']['Total']['Natural sciences']
df = df[['Norway', 'Poland', 'Portugal', 'Russia']]
exp_col = pd.MultiIndex.from_product([['Norway', 'Poland', 'Portugal', 'Russia'],
['Annual']],
names=['GEO', 'FREQ'])
exp_idx = pd.DatetimeIndex(['2009', '2006'], name='TIME_PERIOD')
values = np.array([[20.38, 25.1, 27.77, 38.1],
[25.49, np.nan, 39.05, np.nan]])
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(df, expected)