def test_datatable_update_dataframe_with_make_index(sample_df):
new_df = sample_df.copy().tail(2).reset_index(drop=True)
if dd and isinstance(sample_df, dd.DataFrame):
new_df = dd.from_pandas(new_df, npartitions=1)
dt = DataTable(sample_df,
index='new_index',
make_index=True,
logical_types={'full_name': 'FullName'},
semantic_tags={'phone_number': 'custom_tag'})
original_types = dt.types
dt.update_dataframe(new_df)
assert len(dt._dataframe) == 2
assert dt.index == 'new_index'
pd.testing.assert_frame_equal(original_types, dt.types)
# confirm that DataColumn series matches corresponding dataframe column
for col in dt.columns:
assert to_pandas(dt.columns[col]._series).equals(
to_pandas(dt._dataframe[col]))
assert dt.columns[col]._series.dtype == dt._dataframe[col].dtype
# confirm that we can update using current dataframe without error
dt.update_dataframe(dt._dataframe.head(1))
assert len(dt._dataframe) == 1
def test_underlying_index_on_update(sample_df):
if dd and isinstance(sample_df, dd.DataFrame):
pytest.xfail(
'Setting underlying index is not supported with Dask input')
if ks and isinstance(sample_df, ks.DataFrame):
pytest.xfail(
'Setting underlying index is not supported with Koalas input')
dt = DataTable(sample_df.copy(), index='id')
dt.update_dataframe(sample_df.tail(2))
assert (dt._dataframe.index == [2, 3]).all()
assert dt._dataframe.index.name is None
assert type(dt._dataframe.index) == pd.Int64Index
assert type(dt.to_dataframe().index) == pd.Int64Index
def test_underlying_index_on_update(sample_df):
if dd and isinstance(sample_df, dd.DataFrame):
pytest.xfail(
'Setting underlying index is not supported with Dask input')
if ks and isinstance(sample_df, ks.DataFrame):
pytest.xfail(
'Setting underlying index is not supported with Koalas input')
dt = DataTable(sample_df.copy(), index='id')
dt.update_dataframe(sample_df.tail(2))
assert (dt._dataframe.index == [2, 3]).all()
assert dt._dataframe.index.name is None
assert type(dt._dataframe.index) == pd.Int64Index
assert type(dt.to_dataframe().index) == pd.Int64Index
actual = dt.iloc[[0, 1]]
assert type(actual._dataframe.index) == pd.Index
assert type(actual.to_dataframe().index) == pd.Index
actual = dt.select(dt.index)
assert type(actual._dataframe.index) == pd.Int64Index
assert type(actual.to_dataframe().index) == pd.Int64Index
actual = dt[['age']]
assert type(actual._dataframe.index) == pd.Int64Index
assert type(actual.to_dataframe().index) == pd.Int64Index
actual = dt.drop(dt.index)
assert type(actual._dataframe.index) == pd.RangeIndex
assert type(actual.to_dataframe().index) == pd.RangeIndex
actual = dt.reset_semantic_tags(retain_index_tags=False)
assert type(actual._dataframe.index) == pd.RangeIndex
assert type(actual.to_dataframe().index) == pd.RangeIndex
actual = dt.set_types(retain_index_tags=False,
semantic_tags={'id': 'numeric'})
assert type(actual._dataframe.index) == pd.RangeIndex
assert type(actual.to_dataframe().index) == pd.RangeIndex
dt.pop(dt.index)
assert type(dt._dataframe.index) == pd.RangeIndex
assert type(dt.to_dataframe().index) == pd.RangeIndex
