Let's assume I have a dataset where the variables can be scaled quite differently from each other. I want to create histograms for each of the numeric variables. I am trying to make the x and y scales independent from each other so that the scales will not affect the visual quality. But even when I use resolve_scale()
it only makes the y-scale independent, while x is still common among all the variables. This can be seen from the figure below which can be obtained by applying the code. Is this the desired behavior or am I missing something?
My question is:
1. How can I make the x scale independent?
2. How can I make the title get closer to the plot?
Thanks for your help.
version: python altair 4.0
alt.__version__
'4.0.1'
import altair as alt
data = alt.datasets.load_dataset('flights-2k')
chosen_origin_airports = data.groupby('origin').size().sort_values(ascending=False).head(12).index.tolist()
data = data[data.origin.isin(chosen_origin_airports)]
data.loc[data.origin=='BWI', 'delay'] = data.loc[data.origin=='BWI', 'delay'] * (10000)
alt.Chart(data=data).mark_bar().encode(
x = alt.X('delay:Q',
axis=alt.Axis(title=''),
scale=alt.Scale(zero=False),
bin=alt.Bin(maxbins=20)),
y = alt.Y('count():Q',
axis=alt.Axis(title='')),
color = alt.Color('origin:N')
).properties(
width=130,
height=130
).facet(
alt.Column('origin:N', sort = alt.EncodingSortField(order=None)),
align= 'all',
padding=0,
columns=4,
spacing=0
).properties(
title=''
).configure_title(
fontSize=20,
font='Courier',
anchor='middle',
color='gray',
align='left'
).configure_header(
title=None,
titleColor='green',
titleFontSize=14,
labelColor='forestgreen',
labelFontSize=14
).resolve_axis(
x='independent',
y='independent'
).resolve_scale(
x='independent',
y='independent'
)
Your scales are independent, but your binnings are not. Unfortunately, the Vega-Lite grammar provides no easy way to define a bin transform that applies different bin parameters to different subsets of data, so you'll have to have to manually use a distinct bin transform for each panel of the chart.
I would probably do something like this:
chart = alt.Chart(data).mark_bar().encode(
x = alt.X('delay:Q',
axis=alt.Axis(title=''),
scale=alt.Scale(zero=False),
bin=alt.Bin(maxbins=20)),
y = alt.Y('count():Q',
axis=alt.Axis(title='')),
color = alt.Color('origin:N')
).properties(
width=130,
height=130
)
alt.ConcatChart(
concat=[
chart.transform_filter(alt.datum.origin == value).properties(title=value)
for value in sorted(data.origin.unique())
],
columns=4
).configure_title(
fontSize=20,
font='Courier',
anchor='middle',
color='gray',
align='left'
).resolve_axis(
x='independent',
y='independent'
).resolve_scale(
x='independent',
y='independent'
)