def test_is_dataframe_like():
df = cudf.DataFrame({'x': [1, 2, 3]})
assert is_dataframe_like(df)
assert is_series_like(df.x)
assert is_index_like(df.index)
assert not is_dataframe_like(df.x)
assert not is_series_like(df)
assert not is_index_like(df)
def test_is_dataframe_like(monkeypatch, frame_value_counts):
# When we drop support for pandas 1.0, this compat check can
# be dropped
if frame_value_counts:
monkeypatch.setattr(pd.DataFrame, "value_counts", lambda x: None, raising=False)
df = pd.DataFrame({"x": [1, 2, 3]})
ddf = dd.from_pandas(df, npartitions=1)
assert is_dataframe_like(df)
assert is_dataframe_like(ddf)
assert not is_dataframe_like(df.x)
assert not is_dataframe_like(ddf.x)
assert not is_dataframe_like(df.index)
assert not is_dataframe_like(ddf.index)
assert not is_dataframe_like(pd.DataFrame)
assert not is_series_like(df)
assert not is_series_like(ddf)
assert is_series_like(df.x)
assert is_series_like(ddf.x)
assert not is_series_like(df.index)
assert not is_series_like(ddf.index)
assert not is_series_like(pd.Series)
assert not is_index_like(df)
assert not is_index_like(ddf)
assert not is_index_like(df.x)
assert not is_index_like(ddf.x)
assert is_index_like(df.index)
assert is_index_like(ddf.index)
assert not is_index_like(pd.Index)
# The following checks support of class wrappers, which
# requires the comparions of `x.__class__` instead of `type(x)`
class DataFrameWrapper:
__class__ = pd.DataFrame
wrap = DataFrameWrapper()
wrap.dtypes = None
wrap.columns = None
assert is_dataframe_like(wrap)
class SeriesWrapper:
__class__ = pd.Series
wrap = SeriesWrapper()
wrap.dtype = None
wrap.name = None
assert is_series_like(wrap)
class IndexWrapper:
__class__ = pd.Index
wrap = IndexWrapper()
wrap.dtype = None
wrap.name = None
assert is_index_like(wrap)
def test_is_dataframe_like():
df = pd.DataFrame({'x': [1, 2, 3]})
assert is_dataframe_like(df)
assert not is_dataframe_like(df.x)
assert not is_dataframe_like(df.index)
assert not is_series_like(df)
assert is_series_like(df.x)
assert not is_series_like(df.index)
assert not is_index_like(df)
assert not is_index_like(df.x)
assert is_index_like(df.index)
ddf = dd.from_pandas(df, npartitions=1)
assert is_dataframe_like(ddf)
def test_is_dataframe_like(monkeypatch, frame_value_counts):
# When we drop support for pandas 1.0, this compat check can
# be dropped
if frame_value_counts:
monkeypatch.setattr(pd.DataFrame,
"value_counts",
lambda x: None,
raising=False)
df = pd.DataFrame({"x": [1, 2, 3]})
ddf = dd.from_pandas(df, npartitions=1)
assert is_dataframe_like(df)
assert is_dataframe_like(ddf)
assert not is_dataframe_like(df.x)
assert not is_dataframe_like(ddf.x)
assert not is_dataframe_like(df.index)
assert not is_dataframe_like(ddf.index)
assert not is_dataframe_like(pd.DataFrame)
assert not is_series_like(df)
assert not is_series_like(ddf)
assert is_series_like(df.x)
assert is_series_like(ddf.x)
assert not is_series_like(df.index)
assert not is_series_like(ddf.index)
assert not is_series_like(pd.Series)
assert not is_index_like(df)
assert not is_index_like(ddf)
assert not is_index_like(df.x)
assert not is_index_like(ddf.x)
assert is_index_like(df.index)
assert is_index_like(ddf.index)
assert not is_index_like(pd.Index)
def test_is_dataframe_like():
df = pd.DataFrame({'x': [1, 2, 3]})
ddf = dd.from_pandas(df, npartitions=1)
assert is_dataframe_like(df)
assert is_dataframe_like(ddf)
assert not is_dataframe_like(df.x)
assert not is_dataframe_like(ddf.x)
assert not is_dataframe_like(df.index)
assert not is_dataframe_like(ddf.index)
assert not is_dataframe_like(pd.DataFrame)
assert not is_series_like(df)
assert not is_series_like(ddf)
assert is_series_like(df.x)
assert is_series_like(ddf.x)
assert not is_series_like(df.index)
assert not is_series_like(ddf.index)
assert not is_series_like(pd.Series)
assert not is_index_like(df)
assert not is_index_like(ddf)
assert not is_index_like(df.x)
assert not is_index_like(ddf.x)
assert is_index_like(df.index)
assert is_index_like(ddf.index)
assert not is_index_like(pd.Index)
def cummax_aggregate(x, y):
if is_series_like(x) or is_dataframe_like(x):
return x.where((x > y) | x.isnull(), y, axis=x.ndim - 1)
else: # scalar
return x if x > y else y
