srowen commented on a change in pull request #26596: [SPARK-29959][ML][PYSPARK] Summarizer support more metrics URL: https://github.com/apache/spark/pull/26596#discussion_r348510940
########## File path: docs/ml-statistics.md ########## @@ -109,7 +109,8 @@ Refer to the [`ChiSquareTest` Python docs](api/python/index.html#pyspark.ml.stat ## Summarizer We provide vector column summary statistics for `Dataframe` through `Summarizer`. -Available metrics are the column-wise max, min, mean, variance, and number of nonzeros, as well as the total count. +Available metrics are the column-wise max, min, mean, sum, variance, std, squared sum, and number of nonzeros, Review comment: I can see providing the sum maybe, but sum of squares (not squared sum right?)? is that useful? I know it's _available_ as a statistic, but i think the question is what will people expect to see here as compared to say https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.describe.html This doesn't provide sum although it provides percentiles, but I don't know if we should compute those. ---------------------------------------------------------------- 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: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
