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Exponentially weighted moving averages in mlr step -a ewma: principally useful for smoothing of noisy time series, e.g. finely sampled system-resource utilization to give one of many possible examples. Please see http://johnkerl.org/miller/doc/reference.html#step.
"Horizontal" univariate statistics in mlr merge-fields, compared to mlr stats which is "vertical". Also allows collapsing multiple fields into one, such as in_bytes and out_bytes data fields summing to bytes_sum. This can also be done easily using mlr put. However, mlr merge-fields allows aggregation of more than just a pair of field names, and supports pattern-matching on field names. Please see http://johnkerl.org/miller/doc/reference.html#merge-fields for more information.
isnull and isnotnull functions for mlr filter and mlr put.
stats1, stats2, merge-fields, step, and top correctly handle not only missing fields (in the row-heterogeneous-data case) but also null-valued fields.