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TST: Remove tm.get_data_path use #566

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Aug 13, 2018
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TST: Remove tm.get_data_path use #566

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1 change: 1 addition & 0 deletions docs/source/whatsnew.rst
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Expand Up @@ -18,6 +18,7 @@ What's New

These are new features and improvements of note in each release.

.. include:: whatsnew/v0.7.0.txt
.. include:: whatsnew/v0.6.0.txt
.. include:: whatsnew/v0.5.0.txt
.. include:: whatsnew/v0.4.0.txt
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3 changes: 2 additions & 1 deletion docs/source/whatsnew/v0.7.0.txt
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Expand Up @@ -71,7 +71,8 @@ Bug Fixes
- Updated Google Daily Price API to functional url (:issue:`502`)
- Fix Yahoo! price data (:issue:`498`)
- Added back support for Yahoo! price, dividends, and splits data for stocks
and currency pairs (:issue:`487`).
and currency pairs (:issue:`487`).
- Add `is_list_like` to compatibility layer to avoid failure on pandas >= 0.23 (:issue:`520`)
- Fixed Yahoo! time offset (:issue:`487`).
- Fix Yahoo! quote reader (:issue: `540`)
- Remove import of deprecated `tm.get_data_path` (:issue: `566`)
36 changes: 36 additions & 0 deletions pandas_datareader/conftest.py
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@@ -0,0 +1,36 @@
import os

import pytest


@pytest.fixture
def datapath(request):
"""Get the path to a data file.

Parameters
----------
path : str
Path to the file, relative to ``pandas/tests/``

Returns
-------
path : path including ``pandas/tests``.

Raises
------
ValueError
If the path doesn't exist and the --strict-data-files option is set.
"""
BASE_PATH = os.path.join(os.path.dirname(__file__), 'tests')

def deco(*args):
path = os.path.join(BASE_PATH, *args)
if not os.path.exists(path):
if request.config.getoption("--strict-data-files"):
msg = "Could not find file {} and --strict-data-files is set."
raise ValueError(msg.format(path))
else:
msg = "Could not find {}."
pytest.skip(msg.format(path))
return path
return deco
137 changes: 69 additions & 68 deletions pandas_datareader/tests/io/test_jsdmx.py
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Expand Up @@ -7,79 +7,80 @@
import pandas.util.testing as tm
import pytest

from pandas_datareader.io import read_jsdmx
from pandas_datareader.compat import PANDAS_0210
from pandas_datareader.io import read_jsdmx


@pytest.fixture
def dirpath(datapath):
return datapath("io", "data")

class TestJSDMX(object):

def setup_method(self, method):
self.dirpath = tm.get_data_path()
@pytest.mark.skipif(not PANDAS_0210, reason='Broken on old pandas')
def test_tourism(dirpath):
# OECD -> Industry and Services -> Inbound Tourism
result = read_jsdmx(os.path.join(dirpath, 'jsdmx',
'tourism.json'))
assert isinstance(result, pd.DataFrame)
jp = result['Japan']
visitors = ['China', 'Hong Kong, China',
'Total international arrivals',
'Korea', 'Chinese Taipei', 'United States']

@pytest.mark.skipif(not PANDAS_0210, reason='Broken on old pandas')
def test_tourism(self):
# OECD -> Industry and Services -> Inbound Tourism
result = read_jsdmx(os.path.join(self.dirpath, 'jsdmx',
'tourism.json'))
assert isinstance(result, pd.DataFrame)
jp = result['Japan']
visitors = ['China', 'Hong Kong, China',
'Total international arrivals',
'Korea', 'Chinese Taipei', 'United States']
exp_col = pd.Index(
['China', 'Hong Kong, China', 'Total international arrivals',
'Korea', 'Chinese Taipei', 'United States'],
name='Variable')
exp_idx = pd.DatetimeIndex(['2008-01-01', '2009-01-01', '2010-01-01',
'2011-01-01', '2012-01-01', '2013-01-01',
'2014-01-01', '2015-01-01', '2016-01-01'],
name='Year')
values = [
[1000000.0, 550000.0, 8351000.0, 2382000.0, 1390000.0, 768000.0],
[1006000.0, 450000.0, 6790000.0, 1587000.0, 1024000.0, 700000.0],
[1413000.0, 509000.0, 8611000.0, 2440000.0, 1268000.0, 727000.0],
[1043000.0, 365000.0, 6219000.0, 1658000.0, 994000.0, 566000.0],
[1430000.0, 482000.0, 8368000.0, 2044000.0, 1467000.0, 717000.0],
[1314000.0, 746000.0, 10364000.0, 2456000.0, 2211000.0, 799000.0],
[2409000.0, 926000.0, 13413000.0, 2755000.0, 2830000.0, 892000.0],
[4993689.0, 1524292.0, 19737409.0, 4002095.0, 3677075.0,
1033258.0],
[6373564.0, 1839193.0, 24039700.0, 5090302.0, 4167512.0, 1242719.0]
]
values = np.array(values, dtype='object')
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(jp[visitors], expected)

exp_col = pd.Index(
['China', 'Hong Kong, China', 'Total international arrivals',
'Korea', 'Chinese Taipei', 'United States'],
name='Variable')
exp_idx = pd.DatetimeIndex(['2008-01-01', '2009-01-01', '2010-01-01',
'2011-01-01', '2012-01-01', '2013-01-01',
'2014-01-01', '2015-01-01', '2016-01-01'],
name='Year')
values = [
[1000000.0, 550000.0, 8351000.0, 2382000.0, 1390000.0, 768000.0],
[1006000.0, 450000.0, 6790000.0, 1587000.0, 1024000.0, 700000.0],
[1413000.0, 509000.0, 8611000.0, 2440000.0, 1268000.0, 727000.0],
[1043000.0, 365000.0, 6219000.0, 1658000.0, 994000.0, 566000.0],
[1430000.0, 482000.0, 8368000.0, 2044000.0, 1467000.0, 717000.0],
[1314000.0, 746000.0, 10364000.0, 2456000.0, 2211000.0, 799000.0],
[2409000.0, 926000.0, 13413000.0, 2755000.0, 2830000.0, 892000.0],
[4993689.0, 1524292.0, 19737409.0, 4002095.0, 3677075.0,
1033258.0],
[6373564.0, 1839193.0, 24039700.0, 5090302.0, 4167512.0, 1242719.0]
]
values = np.array(values, dtype='object')
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(jp[visitors], expected)

@pytest.mark.skipif(not PANDAS_0210, reason='Broken on old pandas')
def test_land_use(self):
# OECD -> Environment -> Resources Land Use
result = read_jsdmx(os.path.join(self.dirpath, 'jsdmx',
'land_use.json'))
assert isinstance(result, pd.DataFrame)
result = result.loc['2010':'2011']
@pytest.mark.skipif(not PANDAS_0210, reason='Broken on old pandas')
def test_land_use(dirpath):
# OECD -> Environment -> Resources Land Use
result = read_jsdmx(os.path.join(dirpath, 'jsdmx',
'land_use.json'))
assert isinstance(result, pd.DataFrame)
result = result.loc['2010':'2011']

cols = ['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']
exp_col = pd.MultiIndex.from_product([
['Japan', 'United States'],
cols], names=['Country', 'Variable'])
exp_idx = pd.DatetimeIndex(['2010', '2011'], name='Year')
values = [
[53790.0, 14.753154141525, 377800.0, np.nan, np.nan, 364600.0,
5000.0, 1.3713658804169, np.nan, np.nan,
1897990.0, 20.722767650476, 9629090.0, np.nan, np.nan, 9158960.0,
2416000.0, 26.378540795025, np.nan,
np.nan],
[53580.0, 14.691527282698, 377800.0, np.nan, np.nan, 364700.0,
5000.0, 1.3709898546751, np.nan, np.nan,
1897990.0, 20.722767650476, 9629090.0, np.nan, np.nan, 9158960.0,
2416000.0, 26.378540795025, np.nan,
np.nan]]
values = np.array(values)
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(result[exp_col], expected)
cols = ['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']
exp_col = pd.MultiIndex.from_product([
['Japan', 'United States'],
cols], names=['Country', 'Variable'])
exp_idx = pd.DatetimeIndex(['2010', '2011'], name='Year')
values = [
[53790.0, 14.753154141525, 377800.0, np.nan, np.nan, 364600.0,
5000.0, 1.3713658804169, np.nan, np.nan,
1897990.0, 20.722767650476, 9629090.0, np.nan, np.nan, 9158960.0,
2416000.0, 26.378540795025, np.nan,
np.nan],
[53580.0, 14.691527282698, 377800.0, np.nan, np.nan, 364700.0,
5000.0, 1.3709898546751, np.nan, np.nan,
1897990.0, 20.722767650476, 9629090.0, np.nan, np.nan, 9158960.0,
2416000.0, 26.378540795025, np.nan,
np.nan]]
values = np.array(values)
expected = pd.DataFrame(values, index=exp_idx, columns=exp_col)
tm.assert_frame_equal(result[exp_col], expected)
47 changes: 24 additions & 23 deletions pandas_datareader/tests/io/test_sdmx.py
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Expand Up @@ -5,36 +5,37 @@
import numpy as np
import pandas as pd
import pandas.util.testing as tm
import pytest

from pandas_datareader.io.sdmx import read_sdmx, _read_sdmx_dsd


class TestSDMX(object):
@pytest.fixture
def dirpath(datapath):
return datapath("io", "data")

def setup_method(self, method):
self.dirpath = tm.get_data_path()

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)
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)
assert isinstance(df, pd.DataFrame)
assert df.shape == (2, 336)

df = df['Percentage']['Total']['Natural sciences']
df = df[['Norway', 'Poland', 'Portugal', 'Russia']]
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')
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)
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)
8 changes: 4 additions & 4 deletions pandas_datareader/tests/yahoo/test_options.py
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Expand Up @@ -50,17 +50,17 @@ def expiry(month, year):


@pytest.fixture
def json1():
dirpath = tm.get_data_path()
def json1(datapath):
dirpath = datapath('yahoo', 'data')
json1 = 'file://' + os.path.join(
dirpath, 'yahoo_options1.json')
return json1


@pytest.fixture
def json2():
def json2(datapath):
# see gh-22: empty table
dirpath = tm.get_data_path()
dirpath = datapath('yahoo', 'data')
json2 = 'file://' + os.path.join(
dirpath, 'yahoo_options2.json')
return json2
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