Add new features as tips

05-transforms.qmd

@@ -295,6 +295,9 @@ values are `missing`. This is the purpose of the `DropMissing` transform:
 georef((a=[1,missing,3], b=[4,5,6])) |> DropMissing()
 ```
 
+The `DropNaN` is an alternative to drop all rows for which the selected column values
+are `NaN`.
+
 ### Statistical
 
 The framework provides various feature transforms for statistical analysis. We will

09-geojoins.qmd

@@ -109,6 +109,11 @@ In database-style join, the predicate function `isequal` is applied to arbitrary
 columns of tables. In `geojoin`, **geometric predicate** functions are applied to
 the `geometry` column of geotables.
 
+The `tablejoin` function can be used for database-style join between a geotable
+and a simple table (e.g., `DataFrame`). The result will be a new geotable over a
+subset of geometries from the first argument. Please check the documentation for
+more details.
+
 :::
 
 ::: {.callout-note}

11-interpolation.qmd

@@ -272,6 +272,16 @@ hundreds of thousands of measurements and very large grids.
 
 :::
 
+::: {.callout-note}
+
+## Tip for all users
+
+The `InterpolateMissing` transform can be used to interpolate `missing`
+values in a geotable using the same algorithm of `InterpolateNeighbors`.
+Likewise, the `InterpolateNaN` can be used to interpolate `NaN` values.
+
+:::
+
 ## Congratulations!
 
 Congratulations on finishing **Part IV** of the book. The interpolation