Merge branch 'main' into 18136-accordion

.github/workflows/typescript-check.yml

@@ -0,0 +1,27 @@
+name: Check TypeScript types
+
+on:
+  push:
+    branches:
+      - main
+      - 'release/**'
+      - 'feature/**'
+  pull_request:
+    branches:
+      - main
+      - 'release/**'
+      - 'feature/**'
+
+jobs:
+  typescript-check:
+    runs-on: ubuntu-latest
+    concurrency:
+      group: ${{ github.workflow }}-${{ github.ref }}
+      cancel-in-progress: true
+    steps:
+      - uses: actions/checkout@v4
+      - name: Install dependencies
+        run: npm ci
+      - name: Check TypeScript types
+        run: python tools/check_typescript_ci.py
+

plugins/dashboard-object-viewer/src/js/src/DashboardPlugin/DashboardPlugin.tsx

@@ -28,7 +28,7 @@ export function DashboardPlugin({
       widget: VariableDefinition;
     }) => {
       const { id: widgetId, name, type } = widget;
-      if (type === dh.VariableType.TABLE || type === dh.VariableType.FIGURE) {
+      if (type === 'Table' || type === 'Figure') {
         // Just ignore table and figure types - only want interesting other types
         return;
       }

plugins/plotly-express/docs/indicator.md

@@ -0,0 +1,273 @@
+# Indicator Plot
+
+An indicator plot is a type of plot that highlights a collection of numeric values.
+
+### What are indicator plots useful for?
+
+- **Highlight specific metrics**: Indicator plots are useful when you want to highlight specific numeric metrics in a visually appealing way.
+- **Compare metrics to a reference value**: Indicator plots are useful to compare metrics to a reference value, such as a starting value or a target value.
+- **Compare metrics to each other**: Indicator plots are useful to compare multiple metrics to each other by highlighting where they fall relative to each other.
+
+## Examples
+
+### A basic indicator plot
+
+Visualize a single numeric value by passing the column name to the `value` argument. The table should contain only one row.
+
+```python
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])
+
+indicator_plot = dx.indicator(dog_avg, value="Price")
+```
+
+### A delta indicator plot
+
+Visualize a single numeric value with a delta to a reference value by passing the reference column name to the `reference` argument.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+dog_agg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price"), agg.first(cols="StartingPrice = Price")])
+
+indicator_plot = dx.indicator(dog_agg, value="Price", reference="StartingPrice")
+```
+
+## Indicator plots from variables
+
+Pass variables into a table to create an indicator plot.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+from deephaven import new_table
+from deephaven.column import int_col
+
+my_value = 10
+my_reference = 5
+
+my_table = new_table([
+    int_col("MyValue", [my_value]),
+    int_col("MyReference", [my_reference])
+])
+
+indicator_plot = dx.indicator(my_table, value="MyValue", reference="MyReference")
+```
+
+# Delta only indicator plot
+
+Visualize only the delta to a reference value by passing `number=False`.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+dog_agg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price"), agg.first(cols="StartingPrice = Price")])
+
+indicator_plot = dx.indicator(dog_agg, value="Price", reference="StartingPrice", number=False)
+```
+
+### An angular indicator plot
+
+Visualize a single numeric value with an angular gauge by passing `gauge="angular"`.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])
+
+indicator_plot = dx.indicator(dog_avg, value="Price", gauge="angular")
+```
+
+### A hidden axis bullet indicator plot
+
+Visualize a single numeric value with a bullet gauge by passing `gauge="bullet"`. Hide the axis by passing `axis=False`.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])
+
+indicator_plot = dx.indicator(dog_avg, value="Price", gauge="bullet", axis=False)
+```
+
+### Prefixes and suffixes
+
+Add a prefix and suffix to the numeric value by passing `prefix` and `suffix`.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])
+
+indicator_plot = dx.indicator(dog_avg, value="Price", prefix="$", suffix="USD")
+```
+
+### Delta Symbols
+
+Modify the symbol before the delta value by passing `increasing_text` and `decreasing_text`.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])
+
+indicator_plot = dx.indicator(dog_avg, value="Price", increasing_text="Up: ", decreasing_text="Down: ")
+```
+
+### Indicator with text
+
+Add text to the indicator by passing the text column name to the `text` argument.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+my_table = dx.data.stocks()
+
+# subset data and aggregate prices, keeping the Sym
+dog_avg = my_table.where("Sym = `DOG`").agg_by([agg.avg(cols="Price")])
+
+indicator_plot = dx.indicator(dog_avg, value="Price", text="Sym")
+```
+
+### Multiple indicators
+
+Visualize multiple numeric values by passing in a table with multiple rows. By default, a square grid of indicators is created.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+my_table = dx.data.stocks()
+
+# aggregate for average prices by Sym
+sym_avg = my_table.agg_by([agg.avg(cols="Price")], by="Sym")
+
+indicator_plot = dx.indicator(sym_avg, value="Price")
+```
+
+### Multiple rows
+
+By default, a grid of indicators is created. To create a specific amount of rows with a dynamic number of columns, pass the number of rows to the `rows` argument.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+my_table = dx.data.stocks()
+
+# aggregate for average prices by Sym
+sym_avg = my_table.agg_by([agg.avg(cols="Price")], by="Sym")
+
+indicator_plot = dx.indicator(sym_avg, value="Price", rows=2)
+```
+
+### Multiple columns
+
+By default, a grid of indicators is created. To create a specific amount of columns with a dynamic number of rows, pass the number of columns to the `columns` argument.
+
+```python order=indicator_plot,my_table
+import deephaven.plot.express as dx
+my_table = dx.data.stocks()
+
+# aggregate for average prices by Sym
+sym_avg = my_table.agg_by([agg.avg(cols="Price")], by="Sym")
+
+indicator_plot = dx.indicator(sym_avg, value="Price", columns=2)
+```
+
+### Delta colors
+
+Change the color of the delta value based on whether it is increasing or decreasing by passing `increasing_color_sequence` and `decreasing_color_sequence`.
+These colors are applied sequentially to the indicators and looped if there are more indicators than colors.
+
+```python
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+sym_agg = my_table.agg_by(
+    [agg.avg(cols="Price"), agg.first(cols="StartingPrice = Price")]
+)
+
+indicator_plot = dx.indicator(
+    sym_agg,
+    value="Price",
+    reference="Starting Price",
+    increasing_color_sequence=["green", "darkgreen"],
+    decreasing_color_sequence=["red", "darkred"],
+)
+```
+
+### Gauge colors
+
+Change the color of the gauge based on the value by passing `gauge_color_sequence`.
+These colors are applied sequentially to the indicators and looped if there are more indicators than colors.
+
+```python
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+
+my_table = dx.data.stocks()
+
+# subset data and aggregate for DOG prices
+sym_agg = my_table.agg_by([agg.avg(cols="Price")])
+
+indicator_plot = dx.indicator(
+    sym_agg, value="Price", gauge_color_sequence=["green", "darkgreen"]
+)
+```
+
+### Plot by
+
+Create groups of styled indicators by passing the grouping categorical column name to the `by` argument.
+`increasing_color_map` and `decreasing_color_map` can be used to style the indicators based on the group.
+
+```python
+import deephaven.plot.express as dx
+from deephaven import agg as agg
+
+my_table = dx.data.stocks()
+
+# subset data and aggregate prices, keeping the Sym
+sym_agg = my_table.agg_by(
+    [
+        agg.avg(cols="Price"),
+        agg.first(cols="StartingPrice = Price"),
+        agg.last(cols="Sym"),
+    ]
+)
+
+indicator_plot = dx.indicator(
+    sym_agg,
+    value="Price",
+    reference="StartingPrice",
+    by="Sym",
+    increasing_color_map={"DOG": "darkgreen"},
+    decreasing_color_map={"DOG": "darkred"},
+)
+```
+
+## API Reference
+```{eval-rst}
+.. dhautofunction:: deephaven.plot.express.indicator
+```

plugins/plotly-express/docs/sidebar.json

@@ -16,6 +16,7 @@
       },
       {
         "label": "Plot Types",
+        "collapsible": false,
         "items": [
           {
             "label": "Area",
@@ -117,6 +118,7 @@
       },
       {
         "label": "Concepts",
+        "collapsible": false,
         "items": [
           {
             "label": "Plot by",