New version (0.32.1) and update docs (#554)

* bump version to ~0.33.0~ 0.32.1

* build docs on 1.3; test on (pre-)release (1.3 and 1.4), drop 1.2

* fix doctests

* release is non-breaking, using 0.24 documenter exactly

.travis.yml

@@ -4,7 +4,8 @@ os:
   - osx
 julia:
   - 1.0
-  - 1.2
+  - 1.3
+  - 1.4
   - nightly
 notifications:
   email: false
@@ -20,7 +21,7 @@ after_success:
 jobs:
   include:
     - stage: "Documentation"
-      julia: 1.0
+      julia: 1.3
       os: linux
       script:
         - julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd()));

Project.toml

@@ -1,7 +1,7 @@
 name = "StatsBase"
 uuid = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 authors = ["JuliaStats"]
-version = "0.32.0"
+version = "0.32.1"
 
 [deps]
 DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"

docs/Project.toml

@@ -1,5 +1,6 @@
 [deps]
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
 [compat]
-Documenter = "~0.22"
+Documenter = "0.24"

src/hist.jl

@@ -134,6 +134,8 @@ Histograms can be fitted to data using the `fit` method.
 # Examples
 ## Example illustrating `closed`
 ```jldoctest
+julia> using StatsBase
+
 julia> fit(Histogram, [2.],  1:3, closed=:left)
 Histogram{Int64,1,Tuple{UnitRange{Int64}}}
 edges:

src/misc.jl

@@ -127,8 +127,8 @@ julia> using StatsBase
 
 julia> indicatormat([1 2 2], 2)
 2×3 Array{Bool,2}:
-  true  false  false
- false   true   true
+ 1  0  0
+ 0  1  1
 ```
 """
 function indicatormat(x::IntegerArray, k::Integer; sparse::Bool=false)

src/transformations.jl

@@ -98,7 +98,7 @@ julia> X = [0.0 -0.5 0.5; 0.0 1.0 2.0]
  0.0   1.0  2.0
 
 julia> dt = fit(ZScoreTransform, X, dims=2)
-ZScoreTransform{Float64}(2, [0.0, 1.0], [0.5, 1.0])
+ZScoreTransform{Float64}(2, 2, [0.0, 1.0], [0.5, 1.0])
 
 julia> StatsBase.transform(dt, X)
 2×3 Array{Float64,2}:
@@ -257,7 +257,7 @@ julia> X = [0.0 -0.5 0.5; 0.0 1.0 2.0]
  0.0   1.0  2.0
 
 julia> dt = fit(UnitRangeTransform, X, dims=2)
-UnitRangeTransform{Float64}(2, true, [-0.5, 0.0], [1.0, 0.5])
+UnitRangeTransform{Float64}(2, 2, true, [-0.5, 0.0], [1.0, 0.5])
 
 julia> StatsBase.transform(dt, X)
 2×3 Array{Float64,2}: