Merge pull request #168 from JuliaAI/dev

For a 2.3.1 release

Author: ablaom

Project.toml

@@ -1,7 +1,7 @@
 name = "ScientificTypes"
 uuid = "321657f4-b219-11e9-178b-2701a2544e81"
 authors = ["Anthony D. Blaom <[email protected]>"]
-version = "2.3"
+version = "2.3.1"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"

src/coerce.jl

@@ -162,7 +162,9 @@ DataFrame! does). An error is thrown otherwise. The arguments are the same as
 `coerce`.
 
 """
-coerce!(X, a...;  kw...) = coerce!(Val(ST.trait(X)), X, a...; kw...)
+coerce!(X, a...;  kw...) = begin
+    coerce!(Val(ST.trait(X)), X, a...; kw...)
+end
 
 coerce!(::Val{:other}, X, a...; kw...) =
     throw(CoercionError("`coerce!` is undefined for non-tabular data."))
@@ -198,16 +200,7 @@ function coerce_df!(df, tdict::AbstractDict{<:ColKey, <:Type}; kw...)
     for name in names
         name in keys(tdict) || continue
         coerce_type = tdict[name]
-        # for DataFrames >= 0.19 df[!, name] = coerce(df[!, name], types(name))
-        # but we want something that works more robustly... even for older
-        # DataFrames; the only way to do this is to use the
-        # `df.name = something` but we cannot use setindex! without throwing
-        # a deprecation warning... metaprogramming to the rescue.
-        name_str = "$name"
-        ex = quote
-            $df.$name = coerce($df.$name, $coerce_type, $kw...)
-        end
-        eval(ex)
+        df[!, name] = coerce(df[!, name], coerce_type; kw...)
     end
     return df
 end

test/extra_coercion.jl

@@ -1,8 +1,11 @@
-@testset "issue #7" begin
-    df = DataFrame(x=[1,2,3,4], y=["a","b","c","a"])
+@testset "coerce!" begin
+    df = DataFrame(x=[1,2,3,4],
+                   y=["a","b","c","a"],
+                   z = Union{Missing,Int}[10, 20, 30, 40])
     coerce!(df, Textual=>Finite)
-    @test scitype(df) == Table{Union{ AbstractArray{Count,1},
-                                      AbstractArray{Multiclass{3},1} }}
+    coerce!(df, Union{Missing,Count}=>Count, tight=true) # issue #166
+    @test scitype(df) == Table{Union{AbstractArray{Count,1},
+                                     AbstractArray{Multiclass{3},1} }}
 end
 
 # issue #9