def test_data_timeUnit_field_temporal_fail():
""""'Passes' if it raises a NotImplementedError"""
chart = alt.Chart(df).mark_point().encode(
alt.X(field='combination', type='temporal', timeUnit='month'))
for channel in chart.to_dict()['encoding']:
with pytest.raises(NotImplementedError):
data = _data._locate_channel_data(chart, channel)
def test_data_aggregate_quantitative_fail(column):
""""'Passes' if it raises a NotImplementedError"""
chart = alt.Chart(df).mark_point().encode(
alt.X(field=column, type='quantitative', aggregate='average'))
for channel in chart.to_dict()['encoding']:
with pytest.raises(NotImplementedError):
data = _data._locate_channel_data(chart, channel)
def test_data_timeUnit_shorthand_temporal_fail():
chart = alt.Chart(df).mark_point().encode(alt.X('month(combination):T'))
for channel in chart.to_dict()['encoding']:
with pytest.raises(NotImplementedError):
data = _data._locate_channel_data(chart, channel)
def test_data_value_quantitative():
chart = alt.Chart(df).mark_point().encode(opacity=alt.value(0.5))
for channel in chart.to_dict()['encoding']:
data = _data._locate_channel_data(chart, channel)
assert data == 0.5
def test_data_shorthand_quantitative(column):
chart = alt.Chart(df).mark_point().encode(alt.X(column))
for channel in chart.to_dict()['encoding']:
data = _data._locate_channel_data(chart, channel)
assert list(data) == list(df[column].values)