The pdvega API is rather simplistic at the moment; it doesn’t give easy access to many of the features that Vega-Lite supports. This binding first populates the interval selection with the scale domains, and then uses the selection to drive the scale domains. This vignette has some example plots – for more details on how to make a plot, see the how to build a chart vignette For more about the design philosophy of the package, see the design vignette. Here is a simple scatter-plot created from the cars dataset: First we’ll create an interval selection using the selection_interval() Radio buttons that force only a single selection, Drop down box for selecting a single item from a list. The example below shows this on the S&P500 data. This approach becomes even more powerful when the selection behavior is An interval selection allows you to select chart elements by clicking and dragging. For more information on how to fine-tune selections, including specifying other Vega-Lite using JSON structures to describe visualisations and interactions, which are compiled down to full Vega specifications. To customize the events that trigger legend interaction, expand the bind property to an object, with a single legend property that maps to a Vega event stream. for example, zooming in on a map. Using the interval selection type, we can actually make a plot zoomable and pannable by binding to the scales. clickable legend that will select points by both Origin and number of Interval selections can be bound to their own, Single and multi selections can be bound to. There are three Knowing how we can select/brush part of a dataset, and that we can bind these selections to a scale, we can make focus/context plots. for points outside the selection: As you can see, with this simple change, the color of the points responds The person Alex makes a selection box when the The fields key points to the feature in the data that should be filtered. The selection_interval() function takes a few additional arguments; for Vega v5.0.0. Filter Transform. Knowing how we can select/brush part of a dataset, and that we can bind these selections to a scale, we can make focus/context plots. Interval selections which can be bound to scale. the chart. VegaScope instructs your web browser to use a recent Vega, Vega-Lite, and Vega-Embed version from In multi-view displays, binding shared scales will keep the views synchronized. click. bind… A similar setup can be used to pan and zoom the cells of a scatterplot matrix: When a single or multi selection is projected over only one field or encoding channel, the bind property can be set to legend to populate the selection by interacting with the corresponding legend. to the selection. "[mousedown[event.altKey], mouseup] > mousemove", "[mousedown[event.shiftKey], mouseup] > mousemove", Bindings, Selections, Conditions: Making Charts Interactive, Selections: Building Blocks of Interactions, Compound Charts: Layer, HConcat, VConcat, Repeat, Facet, Altair Internals: Understanding the Library. The keys in the example above are data, mark and encoding. Now I would like that when the user clicks on an item of ListView, its name is shown in label lblSelectedItem. One input element per projection is generated and can be used to manipulate the selection; any direct manipulation interactions (e.g., clicking on the visualization) will similarly update the input element. For convenience, let’s write a quick Python function that will take a selection example we can bind the interval to only the x-axis, and set it such that the above, and horizontally concatenate two versions of this chart: one Also when looking to the underlying created Vega, it doesn't combine the mouse and touch events within a single on directive, but it rather creates two different code blocks. Each selection type has attributes through which its behavior can be selection in the chart. cylinders: By fine-tuning the behavior of selections in this way, they can be used to Force Directed Layout. Streamlit Observable. method which creates such a selection more concisely. chart scales; this is how Altair plots can be made interactive: Because this is such a common pattern, Altair provides the Chart.interactive() ... Have a scatter plot, I know you use bind on the scales for panning and using the wheel to zoom which is great. With an understanding of the selection types and conditions, you can now add data-driven input elements to the charts using the bind option. look at some of the types of selections available in Altair. Therefore I bind Content property of lblSelectedItem to a property of ViewModel variable