@@ -262,6 +262,21 @@ b = Ball((2, 2), 1)
262262geoms = [p, s, t, b]
263263```
264264
265+ ::: {.callout-note}
266+
267+ ## Tip for all users
268+
269+ The GeoStats.jl module reexports the full stack of modules for
270+ geospatial data science in Julia. There is no need to import
271+ modules like Meshes.jl explicitly. You are all set if you
272+ start your script with
273+
274+ ``` julia
275+ using GeoStats
276+ ```
277+
278+ :::
279+
265280Because these geometries are unaware of each other, we place
266281them into a ` GeometrySet ` , informally known in computational
267282geometry as the "soup of geometries" data structure:
@@ -422,8 +437,6 @@ In the [GeoStats.jl](https://github.com/JuliaEarth/GeoStats.jl) framework, this
422437precisely what we get with the ` georef ` function:
423438
424439``` {julia}
425- using GeoStats
426-
427440df = DataFrame(
428441 NAME=["John", "Mary", "Paul", "Anne"],
429442 AGE=[34.0, 12.0, 23.0, 39.0]u"yr",
@@ -542,21 +555,6 @@ for advanced geospatial data science.
542555
543556::: {.callout-note}
544557
545- ## Tip for all users
546-
547- The GeoStats.jl module reexports the full stack of modules for
548- geospatial data science in Julia. There is no need to import
549- modules like Meshes.jl explicitly. You are all set if you
550- start your script with
551-
552- ``` julia
553- using GeoStats
554- ```
555-
556- :::
557-
558- ::: {.callout-note}
559-
560558## Tip for advanced users
561559
562560In Julia, a function is type-stable if the return type is known at compile
0 commit comments