def setUp(self):
try:
import pandas as pd
except:
raise SkipTest('Pandas not available')
patch('pandas')
self.df = pd.DataFrame([[1, 2], [3, 4], [5, 6]], columns=['x', 'y'])
def setUp(self):
super().setUp()
try:
import dask.dataframe as dd
except:
raise SkipTest('Dask not available')
patch('dask')
self.df = dd.from_pandas(self.df, npartitions=2)
self.cat_df = dd.from_pandas(self.cat_df, npartitions=3)
def setUp(self):
try:
import pandas as pd
except:
raise SkipTest('Pandas not available')
self.backend = 'bokeh'
hv.extension(self.backend)
Store.current_backend = self.backend
self.store_copy = OptionTree(sorted(Store.options().items()),
groups=Options._option_groups)
patch('pandas')
self.df = pd.DataFrame([[1, 2, 'A', 0.1], [3, 4, 'B', 0.2], [5, 6, 'C', 0.3]],
columns=['x', 'y', 'category', 'number'])
def setUp(self):
try:
import pandas as pd
except:
raise SkipTest('Pandas not available')
patch('pandas')
self.df = pd.DataFrame([[1, 2], [3, 4], [5, 6]], columns=['x', 'y'])
self.cat_df = pd.DataFrame([[1, 2, 'A'], [3, 4, 'B'], [5, 6, 'C']],
columns=['x', 'y', 'category'])
self.cat_only_df = pd.DataFrame([['A', 'a'], ['B', 'b'], ['C', 'c']],
columns=['upper', 'lower'])
self.time_df = pd.DataFrame({
'time': pd.date_range('1/1/2000', periods=10, tz='UTC'),
'A': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
'B': 'abcdefghij'})
def setUp(self):
try:
import numpy as np
import pandas as pd
except:
raise SkipTest('Pandas not available')
patch('pandas')
self.df = pd.DataFrame([[1, 2], [3, 4], [5, 6]], columns=['x', 'y'])
self.cat_df = pd.DataFrame([[1, 2, 'A'], [3, 4, 'B'], [5, 6, 'C']],
columns=['x', 'y', 'category'])
self.time_df = pd.DataFrame({
'time':
pd.date_range('1/1/2000', periods=5 * 24, freq='1H', tz='UTC'),
'temp':
np.sin(np.linspace(0, 5 * 2 * np.pi, 5 * 24)).cumsum()
})
def setUp(self):
patch('pandas')
self.df = pd.DataFrame([[1, 2], [3, 4], [5, 6]], columns=['x', 'y'])