From c1afce2fcf4dd196d277b3ee5c98f215d9fe76ad Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jos=C3=A9=20A=2E=20S=2E=20Silva?=
 <32930332+mrr00b00t@users.noreply.github.com>
Date: Tue, 5 Oct 2021 17:39:43 -0300
Subject: [PATCH] =?UTF-8?q?Add=20OrderedFactor=20in=20the=20README.md=20ex?=
 =?UTF-8?q?ample.=20Multiclass=20example=20is=20alr=E2=80=A6=20(#6)?=
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* Add OrderedFactor in the README.md example. Multiclass example is already included.

* Update README.md example.
---
 README.md | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 7f9836f..ecc4a31 100644
--- a/README.md
+++ b/README.md
@@ -34,13 +34,19 @@ using TableDistances
 using ScientificTypes
 
 # create an heterogeneous table
-table = (a=1:5, b=rand(5), c=[:A,:B,:C])
+table = (a=1:3, b=rand(3), c=["A", "B", "C"], d=[1, 2, 4])
+(a = 1:3, b = [0.7596581938450753, 0.6952806574889876, 0.6669145844749085], c = ["A", "B", "C"], d = [1, 2, 4])
 
 # adjust the scientific types
-t = coerce(table, :a => Count, :b => Continuous, :c => Multiclass)
+t = coerce(table, :a => Count, :b => Continuous, :c => Multiclass, :d => OrderedFactor)
+(a = 1:3, b = [0.7596581938450753, 0.6952806574889876, 0.6669145844749085], c = CategoricalArrays.CategoricalValue{String, UInt32}["A", "B", "C"], d = CategoricalArrays.CategoricalValue{Int64, UInt32}[1, 2, 4])
 
 # compute the pairwise distance between rows
 D = pairwise(TableDistance(), t)
+3×3 Matrix{Float64}:
+ 0.0      1.09707   1.75
+ 1.09707  0.0       0.902927
+ 1.75     0.902927  0.0
 ```
 
 Default distances from various packages such as