diff --git a/src/main/scala/com/amazon/deequ/VerificationResult.scala b/src/main/scala/com/amazon/deequ/VerificationResult.scala
index b9b450f2..a6b4b37c 100644
--- a/src/main/scala/com/amazon/deequ/VerificationResult.scala
+++ b/src/main/scala/com/amazon/deequ/VerificationResult.scala
@@ -31,6 +31,7 @@ import com.amazon.deequ.repository.SimpleResultSerde
 import org.apache.spark.sql.Column
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.functions.lit
 import org.apache.spark.sql.functions.{col, monotonically_increasing_id}
 
 import java.util.UUID
@@ -144,9 +145,9 @@ object VerificationResult {
     val constraint = constraintResult.constraint
     constraint match {
       case asserted: RowLevelAssertedConstraint =>
-        constraintResult.metric.flatMap(metricToColumn).map(asserted.assertion(_))
+        constraintResult.metric.flatMap(metricToColumn).map(asserted.assertion(_)).orElse(Some(lit(false)))
       case _: RowLevelConstraint =>
-        constraintResult.metric.flatMap(metricToColumn)
+        constraintResult.metric.flatMap(metricToColumn).orElse(Some(lit(false)))
       case _: RowLevelGroupedConstraint =>
         constraintResult.metric.flatMap(metricToColumn)
       case _ => None
@@ -160,7 +161,6 @@ object VerificationResult {
     }
   }
 
-
   private[this] def getSimplifiedCheckResultOutput(
       verificationResult: VerificationResult)
     : Seq[SimpleCheckResultOutput] = {
diff --git a/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala b/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala
index 146579e8..49ab00aa 100644
--- a/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala
+++ b/src/test/scala/com/amazon/deequ/VerificationSuiteTest.scala
@@ -1996,6 +1996,62 @@ class VerificationSuiteTest extends WordSpec with Matchers with SparkContextSpec
   }
 
   "Verification Suite's Row Level Results" should {
+    "yield correct results for invalid column type" in withSparkSession { sparkSession =>
+      import sparkSession.implicits._
+      val df = Seq(
+        ("1", 1, "blue"),
+        ("2", 2, "green"),
+        ("3", 3, "blue"),
+        ("4", 4, "red"),
+        ("5", 5, "purple")
+      ).toDF("id", "id2", "color")
+
+      val idColumn = "id"
+      val id2Column = "id2"
+
+      val minCheckOnInvalidColumnDescription = s"min check on $idColumn"
+      val minCheckOnValidColumnDescription = s"min check on $id2Column"
+      val patternMatchCheckOnInvalidColumnDescription = s"pattern check on $id2Column"
+      val patternMatchCheckOnValidColumnDescription = s"pattern check on $idColumn"
+
+      val minCheckOnInvalidColumn = Check(CheckLevel.Error, minCheckOnInvalidColumnDescription)
+        .hasMin(idColumn, _ >= 3)
+        .isComplete(idColumn)
+      val minCheckOnValidColumn = Check(CheckLevel.Error, minCheckOnValidColumnDescription)
+        .hasMin(id2Column, _ >= 3)
+        .isComplete(id2Column)
+
+      val patternMatchCheckOnInvalidColumn = Check(CheckLevel.Error, patternMatchCheckOnInvalidColumnDescription)
+        .hasPattern(id2Column, "[0-3]+".r)
+      val patternMatchCheckOnValidColumn = Check(CheckLevel.Error, patternMatchCheckOnValidColumnDescription)
+        .hasPattern(idColumn, "[0-3]+".r)
+
+      val checks = Seq(
+        minCheckOnInvalidColumn,
+        minCheckOnValidColumn,
+        patternMatchCheckOnInvalidColumn,
+        patternMatchCheckOnValidColumn
+      )
+
+      val verificationResult = VerificationSuite().onData(df).addChecks(checks).run()
+      val rowLevelResultsDF = VerificationResult.rowLevelResultsAsDataFrame(sparkSession, verificationResult, df)
+      val rowLevelResults = rowLevelResultsDF.collect()
+
+      val minCheckOnInvalidColumnRowLevelResults =
+        rowLevelResults.map(_.getAs[Boolean](minCheckOnInvalidColumnDescription))
+      val minCheckOnValidColumnRowLevelResults =
+        rowLevelResults.map(_.getAs[Boolean](minCheckOnValidColumnDescription))
+      val patternMatchCheckOnInvalidColumnRowLevelResults =
+        rowLevelResults.map(_.getAs[Boolean](patternMatchCheckOnInvalidColumnDescription))
+      val patternMatchCheckOnValidColumnRowLevelResults =
+        rowLevelResults.map(_.getAs[Boolean](patternMatchCheckOnValidColumnDescription))
+
+      minCheckOnInvalidColumnRowLevelResults shouldBe Seq(false, false, false, false, false)
+      minCheckOnValidColumnRowLevelResults shouldBe Seq(false, false, true, true, true)
+      patternMatchCheckOnInvalidColumnRowLevelResults shouldBe Seq(false, false, false, false, false)
+      patternMatchCheckOnValidColumnRowLevelResults shouldBe Seq(true, true, true, false, false)
+    }
+
     "yield correct results for satisfies check" in withSparkSession { sparkSession =>
       import sparkSession.implicits._
       val df = Seq(