diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ReplaceMissingValues.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ReplaceMissingValues.cs
new file mode 100644
index 0000000000..9774e6ae75
--- /dev/null
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ReplaceMissingValues.cs
@@ -0,0 +1,38 @@
+using Microsoft.ML.Data;
+using Microsoft.ML.SamplesUtils;
+
+namespace Microsoft.ML.Samples.Dynamic
+{
+    public static class ReplaceMissingValues
+    {
+        public static void Example()
+        {
+            // Creating the ML.Net IHostEnvironment object, needed for the pipeline.
+            var mlContext = new MLContext();
+
+            // Download the training and validation files.
+            string dataFile = DatasetUtils.DownloadMslrWeb10k();
+
+            // Create the loader to load the data.
+            var loader = mlContext.Data.CreateTextLoader(
+                columns: new[]
+                {
+                    new TextLoader.Column("Label", DataKind.Single, 0),
+                    new TextLoader.Column("GroupId", DataKind.String, 1),
+                    new TextLoader.Column("Features", DataKind.Single, new[] { new TextLoader.Range(2, 138) })
+                }
+            );
+
+            // Load the raw dataset.
+            var data = loader.Load(dataFile);
+
+            // Create the featurization pipeline. First, hash the GroupId column.
+            var pipeline = mlContext.Transforms.Conversion.Hash("GroupId")
+                // Replace missing values in Features column with the default replacement value for its type.
+                .Append(mlContext.Transforms.ReplaceMissingValues("Features"));
+
+            // Fit the pipeline and transform the dataset.
+            var transformedData = pipeline.Fit(data).Transform(data);
+        }
+    }
+}
diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ReplaceMissingValuesColumnOptions.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ReplaceMissingValuesColumnOptions.cs
new file mode 100644
index 0000000000..477bc8d649
--- /dev/null
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ReplaceMissingValuesColumnOptions.cs
@@ -0,0 +1,38 @@
+using Microsoft.ML.Data;
+using Microsoft.ML.SamplesUtils;
+using Microsoft.ML.Transforms;
+
+namespace Microsoft.ML.Samples.Dynamic
+{
+    public static class ReplaceMissingValuesColumnOptions
+    {
+        public static void Example()
+        {
+            // Creating the ML.Net IHostEnvironment object, needed for the pipeline.
+            var mlContext = new MLContext();
+
+            // Download the training and validation files.
+            string dataFile = DatasetUtils.DownloadMslrWeb10k();
+
+            // Create the loader to load the data.
+            var loader = mlContext.Data.CreateTextLoader(
+                columns: new[]
+                {
+                    new TextLoader.Column("Label", DataKind.Single, 0),
+                    new TextLoader.Column("GroupId", DataKind.String, 1),
+                    new TextLoader.Column("Features", DataKind.Single, new[] { new TextLoader.Range(2, 138) })
+                }
+            );
+
+            // Load the raw dataset.
+            var data = loader.Load(dataFile);
+            // Create the featurization pipeline. First, hash the GroupId column.
+            var pipeline = mlContext.Transforms.Conversion.Hash("GroupId")
+                // Replace missing values in Features column with the default replacement value for its type.
+                .Append(mlContext.Transforms.ReplaceMissingValues(new MissingValueReplacingEstimator.ColumnOptions("Features", "Features", MissingValueReplacingEstimator.ColumnOptions.ReplacementMode.Mean)));
+
+            // Fit the pipeline and transform the dataset.
+            var transformedData = pipeline.Fit(data).Transform(data);
+        }
+    }
+}
diff --git a/src/Microsoft.ML.Transforms/ExtensionsCatalog.cs b/src/Microsoft.ML.Transforms/ExtensionsCatalog.cs
index e57dab218e..e42fee60f1 100644
--- a/src/Microsoft.ML.Transforms/ExtensionsCatalog.cs
+++ b/src/Microsoft.ML.Transforms/ExtensionsCatalog.cs
@@ -46,6 +46,13 @@ public static MissingValueIndicatorEstimator IndicateMissingValues(this Transfor
         /// <param name="inputColumnName">Name of column to transform. If set to <see langword="null"/>, the value of the <paramref name="outputColumnName"/> will be used as source.
         /// If not provided, the <paramref name="inputColumnName"/> will be replaced with the results of the transforms.</param>
         /// <param name="replacementKind">The type of replacement to use as specified in <see cref="MissingValueReplacingEstimator.ColumnOptions.ReplacementMode"/></param>
+        /// <example>
+        /// <format type="text/markdown">
+        /// <![CDATA[
+        /// [!code-csharp[ReplaceMissingValues](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ReplaceMissingValues.cs)]
+        /// ]]>
+        /// </format>
+        /// </example>
         public static MissingValueReplacingEstimator ReplaceMissingValues(this TransformsCatalog catalog,
             string outputColumnName,
             string inputColumnName = null,
@@ -58,6 +65,13 @@ public static MissingValueReplacingEstimator ReplaceMissingValues(this Transform
         /// </summary>
         /// <param name="catalog">The transform extensions' catalog.</param>
         /// <param name="columns">The name of the columns to use, and per-column transformation configuraiton.</param>
+        /// <example>
+        /// <format type="text/markdown">
+        /// <![CDATA[
+        /// [!code-csharp[ReplaceMissingValuesColumnOptions](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ReplaceMissingValuesColumnOptions.cs)]
+        /// ]]>
+        /// </format>
+        /// </example>
         public static MissingValueReplacingEstimator ReplaceMissingValues(this TransformsCatalog catalog, params MissingValueReplacingEstimator.ColumnOptions[] columns)
             => new MissingValueReplacingEstimator(CatalogUtils.GetEnvironment(catalog), columns);
     }