diff --git a/metobsapi/tests/test_data_api.py b/metobsapi/tests/test_data_api.py
index 645be8c780294bb1f6cf2f24cf3468025e03a3d6..d2bb3af17e22ee98e50ce2129fc84ee331dacaa1 100644
--- a/metobsapi/tests/test_data_api.py
+++ b/metobsapi/tests/test_data_api.py
@@ -337,6 +337,26 @@ def test_shorthand_one_symbol_json_column(client):
     assert len(res["results"]["timestamps"]) == 9
 
 
+@pytest.mark.usefixtures("influxdb_3_symbols_9_values")
+def test_shorthand_two_symbols_json_column_order_check(client):
+    res1 = _query_with_symbols(client, "air_temp:rel_hum:wind_speed")
+    res2 = _query_with_symbols(client, "rel_hum:air_temp:wind_speed")
+    assert res1["results"]["data"]["air_temp"] == res2["results"]["data"]["air_temp"]
+    assert res1["results"]["data"]["rel_hum"] == res2["results"]["data"]["rel_hum"]
+
+
+def _query_with_symbols(client, symbols: str) -> dict:
+    res = client.get(f"/api/data.json?site=aoss&inst=tower&symbols={symbols}&begin=-00:10:00&order=column")
+    res = json.loads(res.data.decode())
+    assert res["code"] == 200
+    assert res["num_results"] == 9
+    for symbol in symbols.split(":"):
+        assert symbol in res["results"]["data"]
+        assert len(res["results"]["data"][symbol]) == 9
+        assert len(res["results"]["timestamps"]) == 9
+    return res
+
+
 @pytest.mark.parametrize(
     "symbols",
     [
diff --git a/metobsapi/util/query_influx.py b/metobsapi/util/query_influx.py
index 4b35afd10ed0f601623a9ad83165996a506ef0af..bbc2ee3ecc6c85f83d14efef0448a986011726a6 100644
--- a/metobsapi/util/query_influx.py
+++ b/metobsapi/util/query_influx.py
@@ -89,6 +89,8 @@ class QueryHandler:
             else:
                 data_frame = frames_for_inst[0]
                 data_frame = data_frame.drop(columns=["site", "inst"])
+                # get dataframe into the same order that was requested
+                data_frame = data_frame[symbol_names]
             # "_time" should already be set as the index so we don't need to rename it
             new_column_names = [f"{site}.{inst}.{col_name}" for col_name in data_frame.columns]
             data_frame.columns = new_column_names