mstill3 commented on a change in pull request #26299: Fix typo in example documentation URL: https://github.com/apache/spark/pull/26299#discussion_r340739262
########## File path: python/pyspark/sql/session.py ########## @@ -624,20 +624,20 @@ def createDataFrame(self, data, schema=None, samplingRatio=None, verifySchema=Tr will be inferred from ``data``. When ``schema`` is ``None``, it will try to infer the schema (column names and types) - from ``data``, which should be an RDD of :class:`Row`, - or :class:`namedtuple`, or :class:`dict`. + from ``data``, which should be an RDD of either :class:`Row`, + :class:`namedtuple`, or :class:`dict`. When ``schema`` is :class:`pyspark.sql.types.DataType` or a datatype string, it must match the real data, or an exception will be thrown at runtime. If the given schema is not :class:`pyspark.sql.types.StructType`, it will be wrapped into a - :class:`pyspark.sql.types.StructType` as its only field, and the field name will be "value", - each record will also be wrapped into a tuple, which can be converted to row later. + :class:`pyspark.sql.types.StructType` as its only field, and the field name will be "value". + Each record will also be wrapped into a tuple, which can be converted to row later. If schema inference is needed, ``samplingRatio`` is used to determined the ratio of rows used for schema inference. The first row will be used if ``samplingRatio`` is ``None``. :param data: an RDD of any kind of SQL data representation(e.g. row, tuple, int, boolean, Review comment: okay can do! ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org