Github user sjjpo2002 commented on the pull request:
https://github.com/apache/spark/pull/9366#issuecomment-213601727
I have been trying to use correlation on a matrix with many columns.
@NarineK menthioned R like correlation. I wish we had something like what
[pandas](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.corr.html)
offers. It handles missing data automatically. Take a look
[here](http://stackoverflow.com/questions/31619578/numpy-corrcoef-compute-correlation-matrix-while-ignoring-missing-data).
Even the
[corr()](http://spark.apache.org/docs/latest/api/python/pyspark.mllib.html#pyspark.mllib.stat.Statistics)
function from MLlib can not handle missing data. These features are really
missing from SparkSQL:
- Apply correlation on all columns and return a matrix
- Handle missing data automatically like how [pandas
](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.corr.html)does
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