Reputation: 8722
I can create a stacked bar chart by doing the following:
import pandas as pd
import numpy as np
import altair as alt
data = {'First': {('Header-1', 'H1-A'): 'Red',
('Header-1', 'H1-B'): 'Red',
('Header-1', 'H1-C'): 'Red',
('Header-2', 'H2-A'): 'White',
('Header-2', 'H2-B'): 'White',
('Header-2', 'H2-C'): 'Yellow',
('Header-3', 'H3-A'): 'Red',
('Header-3', 'H3-B'): 'White',
('Header-3', 'H3-C'): 'White',
('Header-3', 'H3-D'): 'Yellow'},
'Second': {('Header-1', 'H1-A'): 'White',
('Header-1', 'H1-B'): 'Yellow',
('Header-1', 'H1-C'): 'Yellow',
('Header-2', 'H2-A'): 'Yellow',
('Header-2', 'H2-B'): 'Green',
('Header-2', 'H2-C'): 'Green',
('Header-3', 'H3-A'): 'Green',
('Header-3', 'H3-B'): 'Red',
('Header-3', 'H3-C'): 'Red',
('Header-3', 'H3-D'): 'White'},
'Third': {('Header-1', 'H1-A'): 'Red',
('Header-1', 'H1-B'): 'Green',
('Header-1', 'H1-C'): 'Green',
('Header-2', 'H2-A'): 'Green',
('Header-2', 'H2-B'): 'White',
('Header-2', 'H2-C'): 'White',
('Header-3', 'H3-A'): 'White',
('Header-3', 'H3-B'): 'Green',
('Header-3', 'H3-C'): 'Green',
('Header-3', 'H3-D'): 'Yellow'},
}
df = pd.DataFrame(data)
column_counts = df.apply(pd.Series.value_counts).fillna(0)
column_counts[column_counts.columns] = column_counts[column_counts.columns].astype('int64')
unstacked = pd.DataFrame(column_counts.unstack())
unstacked = unstacked.reset_index()
unstacked.columns = ['category','kind','counts']
alt.Chart( unstacked ).mark_bar().encode(
x='category',
y='sum(counts)',
color='kind'
)
I do have some control over the order of the stacks by doing:
alt.Chart( unstacked ).mark_bar().encode(
x='category',
y='sum(counts)',
color='kind',
order=alt.Order(
'kind',
sort='descending'
)
)
However, the sort parameter of alt.Order only accepts 'ascending' or 'descending'. I would like to customize the order to be Green, Yellow, Red, White.
Is this possible? How?
Upvotes: 6
Views: 2359
Reputation: 86300
There's no way to directly supply a custom stack order, aside from basing it on descending or ascending order of another field. But you can customize this by providing a field with your desired order.
This can be done with a calculate transform in the chart spec (the vega-lite version of this approach for stack order is outlined here) or by pre-processing the data in Pandas.
Here's an example of the preprocessing approach:
unstacked['order'] = unstacked['kind'].replace(
{val: i for i, val in enumerate(['Green', 'Yellow', 'Red', 'White'])}
)
alt.Chart( unstacked ).mark_bar().encode(
x='category',
y='sum(counts)',
color=alt.Color('kind',
# optional: make color order in legend match stack order
sort=alt.EncodingSortField('order', order='descending')
),
order='order', # this controls stack order
)
Upvotes: 10