def test_tourism(self):
# OECD -> Industry and Services -> Inbound Tourism
result = read_jsdmx(os.path.join(self.dirpath, 'jsdmx', 'tourism.json'))
self.assertTrue(isinstance(result, pd.DataFrame))
exp_col = pd.MultiIndex.from_product([['Japan'],
['China', 'Hong Kong, China',
'Total international arrivals',
'Total international receipts',
'International passenger transport receipts',
'International travel receipts',
'Korea', 'Chinese Taipei', 'United States']],
names=['Country', 'Variable'])
exp_idx = pd.DatetimeIndex(['2004', '2005', '2006', '2007', '2008',
'2009', '2010', '2011', '2012'], name='Year')
values = np.array([[616, 300, 6138, 1550, 330, 1220, 1588, 1081, 760],
[653, 299, 6728, 1710, 340, 1370, 1747, 1275, 822],
[812, 352, 7334, 1330, 350, 980, 2117, 1309, 817],
[942, 432, 8347, 1460, 360, 1100, 2601, 1385, 816],
[1000, 550, 8351, 1430, 310, 1120, 2382, 1390, 768],
[1006, 450, 6790, 1170, 210, 960, 1587, 1024, 700],
[1413, 509, 8611, 1350, 190, 1160, 2440, 1268, 727],
[1043, 365, 6219, 1000, 100, 900, 1658, 994, 566],
[1430, 482, 8368, 1300, 100, 1200, 2044, 1467, 717]])
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(result, expected)
def test_land_use(self):
# OECD -> Environment -> Resources Land Use
result = read_jsdmx(
os.path.join(self.dirpath, 'jsdmx', 'land_use.json'))
self.assertTrue(isinstance(result, pd.DataFrame))
result = result.ix['2010':'2011']
exp_col = pd.MultiIndex.from_product(
[['Japan', 'United States'],
[
'Arable land and permanent crops',
'Arable and cropland % land area', 'Total area', 'Forest',
'Forest % land area', 'Land area',
'Permanent meadows and pastures',
'Meadows and pastures % land area', 'Other areas',
'Other % land area'
]],
names=['Country', 'Variable'])
exp_idx = pd.DatetimeIndex(['2010', '2011'], name='Year')
values = np.array([[
45930, 12.601, 377950, 249790, 68.529, 364500, np.nan, np.nan,
68780, 18.87, 1624330, 17.757, 9831510, 3040220, 33.236, 9147420,
2485000, 27.166, 1997870, 21.841
],
[
45610, 12.513, 377955, 249878, 68.554, 364500,
np.nan, np.nan, 69012, 18.933, 1627625, 17.793,
9831510, 3044048, 33.278, 9147420, 2485000,
27.166, 1990747, 21.763
]])
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(result, expected)
def test_tourism(self):
# OECD -> Industry and Services -> Inbound Tourism
result = read_jsdmx(os.path.join(self.dirpath, 'jsdmx',
'tourism.json'))
self.assertTrue(isinstance(result, pd.DataFrame))
exp_col = pd.MultiIndex.from_product(
[['Japan'],
[
'China', 'Hong Kong, China', 'Total international arrivals',
'Total international receipts',
'International passenger transport receipts',
'International travel receipts', 'Korea', 'Chinese Taipei',
'United States'
]],
names=['Country', 'Variable'])
exp_idx = pd.DatetimeIndex([
'2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011',
'2012'
],
name='Year')
values = np.array([[616, 300, 6138, 1550, 330, 1220, 1588, 1081, 760],
[653, 299, 6728, 1710, 340, 1370, 1747, 1275, 822],
[812, 352, 7334, 1330, 350, 980, 2117, 1309, 817],
[942, 432, 8347, 1460, 360, 1100, 2601, 1385, 816],
[1000, 550, 8351, 1430, 310, 1120, 2382, 1390, 768],
[1006, 450, 6790, 1170, 210, 960, 1587, 1024, 700],
[1413, 509, 8611, 1350, 190, 1160, 2440, 1268, 727],
[1043, 365, 6219, 1000, 100, 900, 1658, 994, 566],
[1430, 482, 8368, 1300, 100, 1200, 2044, 1467,
717]])
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(result, expected)
def test_land_use(self):
# OECD -> Environment -> Resources Land Use
result = read_jsdmx(os.path.join(self.dirpath, 'jsdmx', 'land_use.json'))
self.assertTrue(isinstance(result, pd.DataFrame))
result = result.ix['2010':'2011']
exp_col = pd.MultiIndex.from_product([['Japan', 'United States'],
['Arable land and permanent crops',
'Arable and cropland % land area',
'Total area', 'Forest', 'Forest % land area',
'Land area', 'Permanent meadows and pastures',
'Meadows and pastures % land area',
'Other areas', 'Other % land area']],
names=['Country', 'Variable'])
exp_idx = pd.DatetimeIndex(['2010', '2011'], name='Year')
values = np.array([[45930, 12.601, 377950, 249790, 68.529, 364500, np.nan, np.nan,
68780, 18.87, 1624330, 17.757, 9831510, 3040220, 33.236, 9147420,
2485000, 27.166, 1997870, 21.841],
[45610, 12.513, 377955, 249878, 68.554, 364500, np.nan, np.nan,
69012, 18.933, 1627625, 17.793, 9831510, 3044048, 33.278, 9147420,
2485000, 27.166, 1990747, 21.763]])
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(result, expected)
def _read(self, **kwargs):
data = self._requests_get().json()
result = read_jsdmx(data)
# There is data not be sorted by time
result = result.sort_index()
return result
def _read(self, **kwargs):
data = self._requests_get().json()
result = read_jsdmx(data)
# There is data not be sorted by time
result = result.sort_index()
return result
