Visualization

Show missing Boulder observations as gaps and N/A

Read nullable daily counts from CSV and brush a site/date coverage heatmap to explore linked maps and trends across native notebooks and offline HTML.

Download .aner source Download .anernb notebook Download .ipynb notebook

The CSV has 35 synthetic teaching records for six illustrative Boulder sites on October 12–18, 2026. It includes unquoted NA counts, an omitted site/date row, a wholly absent Wednesday, and a measured zero for North on Sunday. These are not municipal observations or monitoring stations. The daily calendar restores the interior missing day as unknown, without guessing outside the source endpoints. Trends break at missing counts; incomplete period totals and comparison groups show N/A. The full site/date coverage heatmap keeps observed zeros distinct from missing cells. Select a cell to focus its site and date across every view; Ctrl, Cmd or Shift toggles that site while focusing the date, and row labels select sites without changing dates. Drag a rectangle across cells to select an inclusive date range and site rows; the preview commits on release. Modifier-drag adds site rows while replacing the shared date window; Escape cancels. Touch keeps scrolling and tapping. Availability colors do not encode count magnitude. Observed subtotals and coverage describe the available observations separately: 13,780 counts across 31 of 42 expected observations for the full week. Unknown map sizes use neutral fixed markers, while a measured zero retains zero area. The same analysis code runs in .aner, .anernb and Jupyter; exported HTML embeds the snapshot and needs no CSV, kernel or packs to view. Rerun ingestion to reflect an edited CSV. Duplicate keys, missing identity or coordinates, and invalid values remain errors.

// Requires the matching dashboard-enabled native development runtime.
// Run from the project root containing examples/fixtures/plot_boulder_missing.csv.
// Synthetic teaching counts and illustrative positions, not municipal observations.
import aner.data
import aner.plot

// Long format: counts may be missing; site/date/position metadata is required.
var schema = data.schema()
schema = data.column(schema, "date", "String", false)
schema = data.column(schema, "site", "String", false)
schema = data.column(schema, "longitude", "Float64", false)
schema = data.column(schema, "latitude", "Float64", false)
schema = data.column(schema, "count", "Float64", true)
let source = data.scan_csv("examples/fixtures/plot_boulder_missing.csv", schema, missing: "NA")
let bounded = data.bounded(source, max_scanned_rows: 11713,
    max_read_bytes: 8388608, timeout_ms: 5000)
let table = data.collect(bounded, max_rows: 11712,
    max_bytes: 4194304, batch_rows: 256)

// No map pack is needed. Positions and daily counts come from the collected table.
let dashboard = plot.site_dashboard_table(table)
    .title("Boulder: missing observations stay missing")
    .caption("Synthetic plot_boulder_missing.csv teaching counts, Oct 12-18 2026. NA and omitted records stay unknown; measured zero is retained. Illustrative sites.")
    .size(width: 1000, height: 600)
dashboard.show()

// Run in a writable folder with a fresh filename; existing files are never replaced.
// The exported snapshot preserves null counts and calendar gaps without reading CSV again.
dashboard.save("boulder-dashboard-missing.html")

Run step by step in VS Code.

The notebook separates observations and chart construction into cells. It opens with empty outputs and shared variables. Map cells state which optional local packs they need.

Install a compatible native Aner executable and VS Code extension using the editor guide. Chart construction and interactive geographic navigation require the matching development runtime and editor.
Download the .anernb notebook and open it in your VS Code project. If it appears as JSON, choose Reopen Editor With… → Aner Notebook.
Select the Aner — notebook kernel and keep Shared variables active. Run code cells from top to bottom, or choose Run All. Later cells reuse observations and chart values from earlier cells. Run cells that need no pack before trying the optional geographic map.
Read the figures below their producing cells. In geographic outputs, drag to pan and use the zoom controls to reveal crowded labels. Static SVG exports retain the initial view. Source observations, units and limitations remain in each caption.

After changing an earlier cell, rerun its dependent cells. Use Aner: Restart Notebook Session, then Run All, for a clean experiment. Saved outputs are historical; reopening the file starts without live variables. The notebook guide explains session state, inspection, and runtime controls.

Run step by step in Jupyter.

Download the .ipynb notebook and open it in a notebook application with the Aner kernel configured. Select Aner and run its cells from top to bottom. The Jupyter guide explains kernel requirements, shared session state and output policies.

The dashboard uses local date and site controls after the producing cell finishes. Notebook trust and script policies determine whether interaction is displayed; the initial SVG and exported HTML provide the documented fallbacks. Optional map pack requirements are stated in the notebook.

Make it your experiment.

With a compatible development runtime installed, save this program as examples/plot_site_dashboard_missing.aner inside a folder for your experiment. Open a terminal in that folder, then check and run the program.

aner check examples/plot_site_dashboard_missing.aner
aner run examples/plot_site_dashboard_missing.aner

The aner command must be on your PATH. Follow the installation guide if your terminal cannot find it.

Requires an updated native Aner development runtime and matching notebook integration supporting missing site dashboard observations. Aner Plot awaits a binary release and is not included in the published research preview; development packages are not offered here. Save the supplied CSV at examples/fixtures/plot_boulder_missing.csv and source at examples/plot_site_dashboard_missing.aner, then run from the project root containing examples. No map pack, credentials or connection is needed by the default analysis. Export uses a fresh boulder dashboard missing.html filename. Only constructing the optional Colorado boundary context needs usa.co.

aner check examples/plot_site_dashboard_missing.aner
aner run examples/plot_site_dashboard_missing.aner

Required fixture filesplot_boulder_missing.csv

Observations are synthetic teaching inputs. Geographic context comes from optional offline boundary packs and does not add street detail or establish observed traffic conditions.

Read the chart and map contracts

Install Aner