Best prompts for VEO3 using data visualization techniques

Using the CSV dataset at {{data_path}} with columns Date (YYYY-MM-DD) and Value, build an interactive time series chart in VEO3 that: 1) plots raw Value as a thin line, 2) overlays a 7-day rolling average as a bold line, 3) highlights anomalies where Value deviates more than 3 standard deviations from the rolling average, 4) includes hover tooltips showing Date, Value, RollingAverage, and AnomalyScore, and 5) provides a date-range brush to zoom. Use distinct colors for raw vs smoothed series and include a short caption summarizing detected anomalies.

Given a dataset at {{data_path}} with columns Category, Segment, and Value, create a grouped bar chart where each Category has side-by-side bars for each Segment. Add a toggle to switch between raw values and percent-normalized values (percent of Category total). Show data labels on bars, a legend for segments, and sort categories by total value descending.

Using {{data_path}} with columns Date, Component, and Value, create a stacked area chart. Sort components consistently in legend, include a stacked percentage view toggle, and ensure hover tooltips show Component, Value, CumulativeTotal, and ComponentPercentOfTotal. Add an option to isolate a single component (fade others).

From {{data_path}} containing X, Y, and Category columns, build an interactive scatter plot that: 1) fits and displays a linear regression with R-squared in the subtitle, 2) colors points by Category and allows toggling categories, 3) enables selecting a region to compute summary stats (mean, std) for selected points, and 4) optionally runs k-means to suggest up to 5 clusters with a cluster membership toggle.

Using {{geojson_path}} for boundaries and {{data_path}} with columns RegionID and Metric, render a choropleth map in VEO3 that: 1) joins data via RegionID, 2) lets the user choose classification method (equal-interval, quantile, custom thresholds), 3) uses a colorblind-friendly sequential palette, 4) includes an adjustable legend and hover popups (RegionName, Metric, Rank), and 5) displays a small histogram of Metric values beside the map.

From {{data_path}} containing Source, Target, and Value columns, build a Sankey diagram that: 1) aggregates duplicate edges, 2) filters out edges below a user-configurable threshold (absolute or percent), 3) displays node totals and edge percent of source on hover, 4) supports reordering nodes left-to-right, and 5) exports the filtered flow table.