diff --git a/python/pyspark/sql/tests.py b/python/pyspark/sql/tests.py
index 49acf0476623e..c144b410bc384 100644
--- a/python/pyspark/sql/tests.py
+++ b/python/pyspark/sql/tests.py
@@ -4579,6 +4579,12 @@ def test_createDataFrame_with_float_index(self):
             self.spark.createDataFrame(
                 pd.DataFrame({'a': [1, 2, 3]}, index=[2., 3., 4.])).distinct().count(), 3)
 
+    def test_no_partition_toPandas(self):
+        # SPARK-32300: toPandas should work from a Spark DataFrame with no partitions
+        pdf = self.spark.sparkContext.emptyRDD().toDF("col1 int").toPandas()
+        self.assertEqual(len(pdf), 0)
+        self.assertEqual(list(pdf.columns), ["col1"])
+
 
 @unittest.skipIf(
     not _have_pandas or not _have_pyarrow,
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala b/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
index a755a6f5e0371..6e4577591dab3 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
@@ -3290,7 +3290,7 @@ class Dataset[T] private[sql](
         val numPartitions = arrowBatchRdd.partitions.length
 
         // Store collection results for worst case of 1 to N-1 partitions
-        val results = new Array[Array[Array[Byte]]](numPartitions - 1)
+        val results = new Array[Array[Array[Byte]]](Math.max(0, numPartitions - 1))
         var lastIndex = -1  // index of last partition written
 
         // Handler to eagerly write partitions to Python in order