def test_data_as_first_argument():
def equals(df1, df2):
return df1.equals(df2)
df = pd.DataFrame({'x': [0, 1, 2, 3, 4, 5], 'y': [0, 0, 1, 1, 2, 3]})
assert equals(define(df.copy(), 'x*2'), df.copy() >> define('x*2'))
assert equals(create(df, 'x*2'), df >> create('x*2'))
assert len(sample_n(df, 5)) == len(df >> sample_n(5))
assert len(sample_frac(df, .3)) == len(df >> sample_frac(.3))
assert equals(select(df, 'x'), df >> select('x'))
assert equals(rename(df.copy(), z='x'), df.copy() >> rename(z='x'))
assert equals(distinct(df), df >> distinct())
assert equals(arrange(df, 'np.sin(x)'), df >> arrange('np.sin(x)'))
assert equals(group_by(df, 'x'), df >> group_by('x'))
assert equals(ungroup(group_by(df, 'x')), df >> group_by('x') >> ungroup())
assert equals(summarize(df, 'sum(x)'), df >> summarize('sum(x)'))
assert equals(query(df, 'x % 2'), df >> query('x % 2'))
assert equals(tally(df, 'x'), df >> tally('x'))
def xsum(gdf):
return [gdf['x'].sum()]
assert equals(do(group_by(df, 'y'), xsum=xsum),
df >> group_by('y') >> do(xsum=xsum))
assert len(head(df, 4) == 4)
assert len(tail(df, 4) == 4)
def test_distinct():
# Index 0, 1, 2, 3, 4, 5, 6
df = pd.DataFrame({'x': [1, 1, 2, 3, 4, 4, 5], 'y': [1, 2, 3, 4, 5, 5, 6]})
I = pd.Index # noqa: E741
result = df >> distinct()
assert result.index.equals(I([0, 1, 2, 3, 4, 6]))
result = df >> distinct(('x', 'y'), z='x+1')
assert result.index.equals(I([0, 1, 2, 3, 4, 6]))
result = df >> distinct('last')
assert result.index.equals(I([0, 1, 2, 3, 5, 6]))
result = df >> distinct(False)
assert result.index.equals(I([0, 1, 2, 3, 6]))
result = df >> distinct(['x'])
assert result.index.equals(I([0, 2, 3, 4, 6]))
result = df >> distinct(['x'], 'last')
assert result.index.equals(I([1, 2, 3, 5, 6]))
result = df >> distinct(z='x%2')
assert result.index.equals(I([0, 2]))
result1 = df >> define(z='x%2') >> distinct(['x', 'z'])
result2 = df >> distinct(['x'], z='x%2')
assert result1.equals(result2)
with pytest.raises(Exception):
df >> distinct(['x'], 'last', 'cause_exception')
def test_distinct(self):
result = self.df >> distinct()
assert isinstance(result, GroupedDataFrame)
