examples

notebook/duckdb-example.qmd

@@ -0,0 +1,69 @@
+---
+title: "duckdb"
+author: Carl Boettiger
+date: "2024-03-06"
+---
+
+```{r message = FALSE}
+library(duckdbfs)
+library(dplyr)
+library(sf)
+```
+
+
+```{r}
+# SQL
+
+pad <- open_dataset("https://data.source.coop/cboettig/pad-us-3/pad-us3-combined.parquet")
+
+pad_meta <- duckdbfs::st_read_meta("https://data.source.coop/cboettig/pad-us-3/pad-us3-combined.fgb", tblname = "pad_meta")
+pad_meta
+```
+
+
+```{r}
+pad |> 
+  filter(State_Nm == "CA") |> 
+  group_by(FeatClass) |> 
+  summarise(total_area = sum(SHAPE_Area),
+            n = n()) |>
+  collect()
+```
+
+```{r}
+duckdbfs::load_spatial()
+```
+
+
+Reading in as a normal tibble, and then converting to a spatial object:
+
+```{r}
+ca_fee <- pad |> 
+  filter(State_Nm == "CA", FeatClass == "Fee") |> 
+  collect()
+
+ca_fee |> st_as_sf(sf_column_name = "geometry", crs = pad_meta$wkt)
+```
+
+Similarly, any normal data frame can be coerced to a spatial `sf` object, e.g.:
+```{r}
+data.frame(lon = c(1,2), lat=c(0,0)) |> st_as_sf(coords = c("lon", "lat"), crs=4326)
+```
+
+
+```{r}
+spatial_ex <- paste0("https://raw.githubusercontent.com/cboettig/duckdbfs/",
+                     "main/inst/extdata/spatial-test.csv") |>
+  open_dataset(format = "csv") 
+
+spatial_ex |>
+  mutate(geometry = st_point(longitude, latitude)) |>
+  to_sf(crs = 4326)
+```
+```{r}
+ca_fee <- pad |> 
+  filter(State_Nm == "CA", FeatClass == "Fee") |> 
+  group_by(Own_Type) |>
+  summarise(total = sum(SHAPE_Area)) |> head(1000) |> collect()
+
+```

notebook/fire-example.qmd

@@ -18,6 +18,8 @@ library(gdalcubes)
 url <- "https://34c031f8-c9fd-4018-8c5a-4159cdff6b0d-cdn-endpoint.azureedge.net/-/media/calfire-website/what-we-do/fire-resource-assessment-program---frap/gis-data/april-2023/fire221gdb.zip?rev=9e3e1e5e61e242d5b2994d666d72a91a&hash=F424990CD64BB7C4CF01C6CE211C0A59"
 download.file(url, "fire221.gdb.zip",  mode="wb")
 
+
+
 unzip("fire221.gdb.zip")
 ```