def test_apply_to_timeseries_with_uni_dim(self):
cumprod = CumProd(mock_dataset.fields.wins)
result = cumprod.apply(dimx2_date_str_df, None)
expected = pd.Series([2] + [0] * 12,
name='$wins',
index=dimx2_date_str_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim(self):
cumprod = CumProd(slicer.metrics.wins)
result = cumprod.apply(cont_uni_dim_df, None)
expected = pd.Series([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
name='$m$wins',
index=cont_uni_dim_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries(self):
cumprod = CumProd(mock_dataset.fields.wins)
result = cumprod.apply(dimx1_date_df, None)
expected = pd.Series([2, 4, 8, 16, 32, 64],
name='$wins',
index=dimx1_date_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim_and_ref(self):
cumprod = CumProd(slicer.metrics.wins)
result = cumprod.apply(cont_uni_dim_ref_df, ElectionOverElection(slicer.dimensions.timestamp))
expected = pd.Series([1., 1, 1, 1, 1, 1, 1, 1, 1, 1],
name='$m$wins_eoe',
index=cont_uni_dim_ref_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim(self):
cumprod = CumProd(slicer.metrics.wins)
result = cumprod.apply(cont_uni_dim_df, None)
expected = pd.Series([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
name='$m$wins',
index=cont_uni_dim_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim_and_ref(self):
cumprod = CumProd(slicer.metrics.wins)
result = cumprod.apply(
cont_uni_dim_ref_df,
ElectionOverElection(slicer.dimensions.timestamp))
expected = pd.Series([1., 1, 1, 1, 1, 1, 1, 1, 1, 1],
name='$m$wins_eoe',
index=cont_uni_dim_ref_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim_and_ref(self):
cumprod = CumProd(mock_dataset.fields.wins)
result = cumprod.apply(
dimx2_date_str_ref_df,
ElectionOverElection(mock_dataset.fields.timestamp))
expected = pd.Series([2.0] + [0.0] * 10,
name='$wins_eoe',
index=dimx2_date_str_ref_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_cummulative_for_delta_percent(self):
dataset = MagicMock()
dataset.table._table_name = "table"
field = Field("value", None)
cumsum = CumProd(field)
reference = Reference(field,
WeekOverWeek,
delta=True,
delta_percent=True)
df = pd.DataFrame.from_dict({
"$value": [55, 60, 108],
"$cumprod(value)": [55, 3300, 356400],
"$value_wow_delta_percent": [10, 20, 8],
})
result = cumsum.apply(df, reference)
pandas.testing.assert_series_equal(pd.Series([10.0, 32.0, 42.56]),
result)