diff --git a/vespa/application.py b/vespa/application.py
index 889e0572..5dc0c501 100644
--- a/vespa/application.py
+++ b/vespa/application.py
@@ -63,25 +63,26 @@ def parse_labeled_data(df):
     return labeled_data
 
 
-def parse_feed_df(df: DataFrame, include_id):
+def parse_feed_df(df: DataFrame, include_id, id_field="id"):
     """
     Convert a df into batch format for feeding
 
     :param df: DataFrame with the following required columns ["id"]. Additional columns are assumed to be fields.
     :param include_id: Include id on the fields to be fed.
+    :param id_field: Name of the column containing the id field.
     :return: List of Dict containing 'id' and 'fields'.
     """
-    required_columns = ["id"]
+    required_columns = [id_field]
     assert all(
         [x in list(df.columns) for x in required_columns]
     ), "DataFrame needs at least the following columns: {}".format(required_columns)
     records = df.to_dict(orient="records")
     batch = [
         {
-            "id": record["id"],
+            "id": record[id_field],
             "fields": record
             if include_id
-            else {k: v for k, v in record.items() if k not in ["id"]},
+            else {k: v for k, v in record.items() if k not in [id_field]},
         }
         for record in records
     ]
@@ -543,16 +544,17 @@ def feed_batch(
             )
         return batch_http_responses
 
-    def feed_df(self, df: DataFrame, include_id: bool = True, **kwargs):
+    def feed_df(self, df: DataFrame, include_id: bool = True, id_field="id", **kwargs):
         """
         Feed data contained in a DataFrame.
 
         :param df: A DataFrame containing a required 'id' column and the remaining fields to be fed.
         :param include_id: Include id on the fields to be fed. Default to True.
+        :param id_field: Name of the column containing the id field.
         :param kwargs: Additional parameters are passed to :func:`feed_batch`.
         :return: List of HTTP POST responses
         """
-        batch = parse_feed_df(df=df, include_id=include_id)
+        batch = parse_feed_df(df=df, include_id=include_id, id_field=id_field)
         return self.feed_batch(batch=batch, **kwargs)
 
     def delete_data(