I know I can create a chart with custom x-axis limits by, for example:
altair.Chart(source).encode(
x=altair.X("whatever", scale=altair.Scale(domain=(left_limit, right_limit))
)
But given a chart that's been created, with all the bells and whistles on the x-axis and whatnot (my actual usage is more complicated than the simple example above), how do I readjust just the x-axis limits of the chart, without having to specify all of the bells and whistles of my x-axis again???
You can access and override the attributes of the chart object after creation like this:
import altair as alt
from vega_datasets import data
source = data.cars.url
chart = alt.Chart(source).mark_circle().encode(
x=alt.X('Horsepower:Q'), #scale=alt.Scale(domain=[0, 250])),
y='Miles_per_Gallon:Q',
)
chart
chart.encoding.x.scale = alt.Scale(domain=[40, 300])
chart
Related
I'm working on a project for a class where I've been creating faceted scatterplots in Altair where each chart is a different type of food. I was wondering if it would be possible to still use these faceted charts but only display one at a time and give the user the ability to toggle between graphs instead of having each graph displayed one after the other?
Here is a rough diagram of what I'm trying to do and here's the code I have now (and what the output looks like at the moment):
import altair as alt
from vega_datasets import data
hover = alt.selection_single(on='mouseover', nearest=True, empty='none')
base = alt.Chart("Food Nutrition Info Compiled.csv").encode(
x='Energ_Kcal:N',
y='Water_(g):Q',
color=alt.condition(hover, 'Type:N', alt.value('lightgray'))
).properties(
width=180,
height=180,
)
points = base.mark_point().add_selection(
hover
)
text = base.mark_text(dy=-5).encode(
text = 'Shrt_Desc:N',
opacity = alt.condition(hover, alt.value(1), alt.value(0))
)
alt.layer(points, text).facet(
'Type:N',
)
Thanks and I hope this makes sense!
Displaying one faceted chart at a time sounds the same as showing a single subset of the data at any one point. This is currently possible by creating a selection that is bound to e.g. a dropdown and the using that with transform_filter:
import altair as alt
from vega_datasets import data
source = data.cars()
dropdown_options = source['Origin'].unique().tolist()
dropdown = alt.binding_select(
options=dropdown_options,
name='Origin '
)
selection = alt.selection_multi(
fields=['Origin'],
value=[{'Origin': dropdown_options[0]}],
bind=dropdown
)
alt.Chart(source).mark_circle().encode(
x=alt.X('Weight_in_lbs:Q', title=''),
y='Horsepower',
color='Origin',
).add_selection(
selection
).transform_filter(
selection
)
I am trying to develop a new data visualization/graphic, and the bubble plot available here is very similar to what I am trying to make in shape:
https://altair-viz.github.io/gallery/table_bubble_plot_github.html
However, the graph I am trying to make involves some shaded bubbles and some filled in. Is there a way to edit this graph so that the bubble marks are not always filled?
Thank you!
You could use the fillOpacity encoding linked to a field in your data and then set the domain and range of its scale, so that only the values you want have a completely transparent fill:
import altair as alt
from vega_datasets import data
source = data.github.url
fill_threshold = 12
alt.Chart(source).mark_circle(
stroke='black'
).encode(
x='hours(time):O',
y='day(time):O',
size='sum(count):Q',
fillOpacity=alt.FillOpacity(
'sum(count):Q',
scale=alt.Scale(
domain=[fill_threshold, fill_threshold + 0.01],
range=[0 ,1]
)
)
)
You can use the fillOpacity and stroke mark properties to make the marks into circles with no fill. For example:
import altair as alt
from vega_datasets import data
source = data.github.url
alt.Chart(source).mark_circle(
fillOpacity=0,
stroke='black'
).encode(
x='hours(time):O',
y='day(time):O',
size='sum(count):Q',
)
I can modify the classic Simple Scatter Plot with Tooltips, to add opacity to marks, but I'd like to legend colors to stay 100% opaque. In the chart I'm trying to make, I have a df with tens of thousands of rows.
import altair as alt
from vega_datasets import data
source = data.cars()
alt.Chart(source).mark_circle(size=60, opacity=0.1).encode(
x='Horsepower',
y='Miles_per_Gallon',
color='Origin'
)
I've tried alt.Legend's symbolOpacity and gradientOpacity to no avail
color=alt.Color(
'Origin:N',
legend=alt.Legend(
# symbolOpacity=1,
gradientOpacity=1,
)
)
As of now, this seems to be a bug with vega-lite. Per #jvp's suggestion, I've filed a bug report here
UPDATE -- IT'S FIXED
I'm trying to recreate something similar to this vega plot in Altair.
I've had luck building the mark_geoshape maps before when binding to something like color, which can be in encode function, but I cannot for the life of me figure out how to bind the slider to the rotate property of the chart, which lives in project.
I presumed I could do something like this, but no luck:
import altair as alt
from vega_datasets import data
# Data generators for the background
sphere = alt.sphere()
graticule = alt.graticule()
# Source of land data
source = alt.topo_feature(data.world_110m.url, 'countries')
slider = alt.binding_range(min=0, max=100, step=1, name='rotate:')
selector = alt.selection_single(name="SelectorName", fields=['rotate'],
bind=slider, init={'rotate': 180})
# Layering and configuring the components
alt.layer(
alt.Chart(sphere).mark_geoshape(),
alt.Chart(graticule).mark_geoshape(stroke='white', strokeWidth=0.5),
alt.Chart(source).mark_geoshape(fill='ForestGreen', stroke='black')
).project(
'orthographic',
).encode(
rotate=['rotate',180,180]
).properties(width=600, height=400, selection=selector).configure_view(stroke=None)
Any help would be much appreciated.
Thanks
leo
There is currently no way to do this in Altair: the Vega-Lite schema only supports constant rotation values. If you wish, you can do this in Vega; there is an example at https://vega.github.io/vega/docs/projections/.
I would like to add points dynamically to a series in spark - highcharts, precisely using Zeppelin.
I am using:
https://github.com/knockdata/spark-highcharts
Does anybody know how to handle a chart after creating it?
Example:
import com.knockdata.spark.highcharts._
import com.knockdata.spark.highcharts.model._
var myChart = highcharts(
bank
.seriesCol("cluster")
.series("x" -> "x", "y" -> "y"))
.subtitle(Subtitle("Example"))
.title(new Title("EXAMPLE"))
.xAxis(XAxis("X"))
.yAxis(YAxis("Y"))
.chart(Chart.scatter)
myChart.plot()
For normal DataFrame, the chart data is created on the time when call highcharts function. The data series is created from DataFrame according the definition you put inside the highcharts function. It can not add data points manually.
While you can use following options to make the chart more suit for your need.
Add bands to xAxis or yAxis
Add line to xAxis or yAxis. It's quite similar to plotBands
Add data labels
Add tooltips