diff --git a/src/daft-connect/src/translation/expr/unresolved_function.rs b/src/daft-connect/src/translation/expr/unresolved_function.rs
index 10e39e7047..ab9eeda871 100644
--- a/src/daft-connect/src/translation/expr/unresolved_function.rs
+++ b/src/daft-connect/src/translation/expr/unresolved_function.rs
@@ -32,6 +32,8 @@ pub fn unresolved_to_daft_expr(f: &UnresolvedFunction) -> eyre::Result<daft_dsl:
             .wrap_err("Failed to handle <= function"),
         ">=" => handle_binary_op(arguments, daft_dsl::Operator::GtEq)
             .wrap_err("Failed to handle >= function"),
+        "and" => handle_binary_op(arguments, daft_dsl::Operator::And)
+            .wrap_err("Failed to handle and function"),
         "isnotnull" => handle_isnotnull(arguments).wrap_err("Failed to handle isnotnull function"),
         "isnull" => handle_isnull(arguments).wrap_err("Failed to handle isnull function"),
         n => bail!("Unresolved function {n} not yet supported"),
diff --git a/tests/connect/test_basic_column.py b/tests/connect/test_basic_column.py
index 95dcb5cdd0..fb1471f8ad 100644
--- a/tests/connect/test_basic_column.py
+++ b/tests/connect/test_basic_column.py
@@ -44,3 +44,60 @@ def test_column_name(spark_session):
 #     df = spark_session.range(10)
 #     df_item = df.select(col("id")[0])
 #     assert df_item.toPandas()["id"].iloc[0] == 0, "getitem should return first element"
+
+
+def test_column_astype(spark_session):
+    df = spark_session.range(10)
+    df_astype = df.select(col("id").astype(StringType()))
+    assert df_astype.schema.fields[0].dataType == StringType(), "astype should change data type"
+
+
+def test_column_between(spark_session):
+    df = spark_session.range(10)
+    df_between = df.select(col("id").between(3, 6).alias("in_range"))
+    assert df_between.toPandas()["in_range"].tolist() == [False, False, False, True, True, True, True, False, False, False]
+
+
+# TODO: Uncomment when string operations are implemented
+# def test_column_string_ops(spark_session):
+#     df_str = spark_session.createDataFrame([("hello",), ("world",)], ["text"])
+#     df_contains = df_str.select(col("text").contains("o").alias("has_o"))
+#     assert df_contains.toPandas()["has_o"].tolist() == [True, True]
+#     df_startswith = df_str.select(col("text").startswith("h").alias("starts_h"))
+#     assert df_startswith.toPandas()["starts_h"].tolist() == [True, False]
+#     df_endswith = df_str.select(col("text").endswith("d").alias("ends_d"))
+#     assert df_endswith.toPandas()["ends_d"].tolist() == [False, True]
+#     df_substr = df_str.select(col("text").substr(1, 2).alias("first_two"))
+#     assert df_substr.toPandas()["first_two"].tolist() == ["he", "wo"]
+
+
+# TODO: Uncomment when struct operations are implemented
+# def test_column_struct_ops(spark_session):
+#     df_struct = spark_session.createDataFrame([
+#         ({"a": 1, "b": 2},),
+#         ({"a": 3, "b": 4},)
+#     ], ["data"])
+#     df_getfield = df_struct.select(col("data").getField("a").alias("a_val"))
+#     assert df_getfield.toPandas()["a_val"].tolist() == [1, 3]
+#     df_dropfields = df_struct.select(col("data").dropFields("a").alias("no_a"))
+#     assert "a" not in df_dropfields.toPandas()["no_a"][0]
+#     df_withfield = df_struct.select(col("data").withField("c", col("data.a") + 10).alias("with_c"))
+#     assert df_withfield.toPandas()["with_c"][0]["c"] == 11
+
+
+# TODO: Uncomment when array operations are implemented
+# def test_column_array_ops(spark_session):
+#     df_array = spark_session.createDataFrame([([1, 2, 3],), ([4, 5, 6],)], ["numbers"])
+#     df_getitem = df_array.select(col("numbers").getItem(0).alias("first"))
+#     assert df_getitem.toPandas()["first"].tolist() == [1, 4]
+
+
+# TODO: Uncomment when when/otherwise operations are implemented
+# def test_column_case_when(spark_session):
+#     df = spark_session.range(10)
+#     df_case = df.select(
+#         col("id").when(col("id") < 5, "low")
+#                 .otherwise("high")
+#                 .alias("category")
+#     )
+#     assert df_case.toPandas()["category"].tolist() == ["low"] * 5 + ["high"] * 5