A very common operation when trying to work with data is to find out the error range for the data. In scientific research, including error ranges is required.
There are two main ways to do this: standard deviation and standard error of the mean. Pandas has an optimized std aggregation method for both dataframe and groupby. However, it does not have an optimized standard error method, meaning users who want to compute error ranges have to rely on the unoptimized scipy method.
Since computing error ranges is such a common operation, I think it would be very useful if there was an optimized sem method like there is for std.
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