diff --git a/docs/mllib-data-types.md b/docs/mllib-data-types.md
index 5066bb2938..eca101132d 100644
--- a/docs/mllib-data-types.md
+++ b/docs/mllib-data-types.md
@@ -317,7 +317,7 @@ Refer to the [`Matrix` Python docs](api/python/pyspark.mllib.html#pyspark.mllib.
 from pyspark.mllib.linalg import Matrix, Matrices
 
 # Create a dense matrix ((1.0, 2.0), (3.0, 4.0), (5.0, 6.0))
-dm2 = Matrices.dense(3, 2, [1, 2, 3, 4, 5, 6])
+dm2 = Matrices.dense(3, 2, [1, 3, 5, 2, 4, 6])
 
 # Create a sparse matrix ((9.0, 0.0), (0.0, 8.0), (0.0, 6.0))
 sm = Matrices.sparse(3, 2, [0, 1, 3], [0, 2, 1], [9, 6, 8])
@@ -624,7 +624,7 @@ from pyspark.mllib.linalg.distributed import CoordinateMatrix, MatrixEntry
 
 # Create an RDD of coordinate entries.
 #   - This can be done explicitly with the MatrixEntry class:
-entries = sc.parallelize([MatrixEntry(0, 0, 1.2), MatrixEntry(1, 0, 2.1), MatrixEntry(6, 1, 3.7)])
+entries = sc.parallelize([MatrixEntry(0, 0, 1.2), MatrixEntry(1, 0, 2.1), MatrixEntry(2, 1, 3.7)])
 #   - or using (long, long, float) tuples:
 entries = sc.parallelize([(0, 0, 1.2), (1, 0, 2.1), (2, 1, 3.7)])