From 5ec27f54c8dc34e3d307bd66dc29585a74e70751 Mon Sep 17 00:00:00 2001
From: kuzand <kuzand@hotmail.com>
Date: Fri, 2 Nov 2018 15:23:51 +0200
Subject: [PATCH 1/4] Added another solution to question 96.

---
 100_Numpy_exercises.md | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/100_Numpy_exercises.md b/100_Numpy_exercises.md
index 14ae2c5..c93c54b 100644
--- a/100_Numpy_exercises.md
+++ b/100_Numpy_exercises.md
@@ -1156,6 +1156,11 @@ T = np.ascontiguousarray(Z).view(np.dtype((np.void, Z.dtype.itemsize * Z.shape[1
 _, idx = np.unique(T, return_index=True)
 uZ = Z[idx]
 print(uZ)
+
+# Another solution, for NumPy >= 1.13
+# Author: Andreas Kouzelis
+uZ = np.unique(Z, axis=0)
+print(uZ)
 ```
 
 #### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★)

From 5b18530d7992b8868a8d614cedf9927be70f907e Mon Sep 17 00:00:00 2001
From: kuzand <kuzand@hotmail.com>
Date: Fri, 2 Nov 2018 15:55:56 +0200
Subject: [PATCH 2/4] Another solution to question 96.

We can use np.unique with axis=0 to return unique rows of an array. For NumPy >= 1.13
---
 100_Numpy_exercises.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/100_Numpy_exercises.md b/100_Numpy_exercises.md
index c93c54b..1e4c220 100644
--- a/100_Numpy_exercises.md
+++ b/100_Numpy_exercises.md
@@ -1157,8 +1157,8 @@ _, idx = np.unique(T, return_index=True)
 uZ = Z[idx]
 print(uZ)
 
-# Another solution, for NumPy >= 1.13
 # Author: Andreas Kouzelis
+# For NumPy >= 1.13
 uZ = np.unique(Z, axis=0)
 print(uZ)
 ```

From 90f676235aa35c8f9861ac1c96684c34d1d312b0 Mon Sep 17 00:00:00 2001
From: kuzand <kuzand@hotmail.com>
Date: Fri, 2 Nov 2018 15:56:53 +0200
Subject: [PATCH 3/4] Update 100_Numpy_exercises.md

---
 100_Numpy_exercises.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/100_Numpy_exercises.md b/100_Numpy_exercises.md
index 1e4c220..c3ff2cc 100644
--- a/100_Numpy_exercises.md
+++ b/100_Numpy_exercises.md
@@ -1158,7 +1158,7 @@ uZ = Z[idx]
 print(uZ)
 
 # Author: Andreas Kouzelis
-# For NumPy >= 1.13
+# NumPy >= 1.13
 uZ = np.unique(Z, axis=0)
 print(uZ)
 ```

From 03b1a408f5eb0b9f0079a2bed0ac7cba3da22c41 Mon Sep 17 00:00:00 2001
From: kuzand <kuzand@hotmail.com>
Date: Fri, 2 Nov 2018 15:57:57 +0200
Subject: [PATCH 4/4] New hint for question 96

---
 100_Numpy_exercises_with_hint.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/100_Numpy_exercises_with_hint.md b/100_Numpy_exercises_with_hint.md
index 43aaccb..e926efa 100644
--- a/100_Numpy_exercises_with_hint.md
+++ b/100_Numpy_exercises_with_hint.md
@@ -606,7 +606,7 @@ np.sqrt(-1) == np.emath.sqrt(-1)
 
 #### 96. Given a two dimensional array, how to extract unique rows? (★★★) 
 
-(**hint**: np.ascontiguousarray)
+(**hint**: np.ascontiguousarray | np.unique)