Closed
Description
There are some places where Altair currently requires a list or an array to be passed and doesn't accept e.g. a pandas index, although this can easily be converted to a list or an array. The errors from this can sometimes be confusing so I suggest that we are more lenient and at least allow passing pandas Indices by converting them to lists automatically. Optionally, we can convert any data structure that has a tolist() method.
In this example the error is quite helpful, although still a bit confusing since indexes and arrays are often uses interchangeable when working with pandas directly
source = data.cars().melt(id_vars=['Origin', 'Name', 'Year', 'Horsepower', 'Cylinders'])
dropdown_options = source['variable'].drop_duplicates() # This line needs explicit conversion
dropdown = alt.binding_select(
options=dropdown_options,
name='X-axis column '
)
selection = alt.selection_point(
fields=['variable'],
value=[{'variable': dropdown_options[0]}],
bind=dropdown
)
alt.Chart(source).mark_circle().encode(
x=alt.X('value:Q', title=''),
y='Horsepower',
color='Origin',
).add_params(
selection
).transform_filter(
selection
)SchemaValidationError: Invalid specification
altair.vegalite.v5.schema.core.BindRadioSelect->options, validating 'type'
{0: 'Miles_per_Gallon', 406: 'Displacement', 812: 'Weight_in_lbs', 1218: 'Acceleration'} is not of type 'array'
In other cases, such as the one below, the traceback is huge and the error message is not at all helpful
import altair as alt
from vega_datasets import data
barley = data.barley()
barley['variety'] = pd.Categorical(
barley['variety'],
ordered=True,
categories=[
'Manchuria',
'No. 457',
'No. 462',
'No. 475',
'Glabron',
'Svansota',
'Velvet',
'Trebi',
'Wisconsin No. 38',
'Peatland'
]
)
alt.Chart(barley).mark_bar().encode(
x=alt.X('variety', sort=barley['variety'].cat.categories), # This line needs manual conversion
y=alt.Y('sum(yield)'),
color='site:N'
)ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
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