nctoolkit.DataSet.tstdev

DataSet.tstdev(over='time', align='right')

tstdev: Calculate the temporal standard deviation of all variables Useful for: monthly standard deviation, annual/yearly standard deviation, seasonal standard deviation, daily standard deviation, daily climatology, monthly climatology, seasonal climatology

Parameters:

• over (str or list) – Time periods to average over. Options are ‘year’, ‘month’, ‘day’. This operates in a similar way to the groupby method in pandas or the tidyverse in R, with over acting as the grouping.

• align (str) – This determines whether the output time is at the left, centre or right hand side of the time window. Options are “left”, “centre” and “right”

Examples

If you want to calculate standard deviation over all time steps. Do the following:

>>> ds.tstdev()

If you want to calculate the standard deviation for each year in a dataset, do this:

>>> ds.tstdev("year")

If you want to calculate the standard deviation for each month in a dataset, do this:

>>> ds.tstdev("month")

If you want to calculate the standard deviation for each month in each year in a dataset, do this:

>>> ds.tstdev(["year", "month"])

This method will also let you easily calculate climatologies. So, if you wanted to calculate a monthly climatological var, you would do this:

>>> ds.tstdev("month")

A daily climatological standard deviation would be the following:

>>> ds.tstdev("day")