Series.aggregate(func, axis=0, *args, **kwargs)
[source]
Aggregate using callable, string, dict, or list of string/callables
New in version 0.20.0.
Parameters: |
func : callable, string, dictionary, or list of string/callables Function to use for aggregating the data. If a function, must either work when passed a Series or when passed to Series.apply. For a DataFrame, can pass a dict, if the keys are DataFrame column names. Accepted Combinations are:
|
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Returns: |
aggregated : Series |
See also
Numpy functions mean/median/prod/sum/std/var are special cased so the default behavior is applying the function along axis=0 (e.g., np.mean(arr_2d, axis=0)) as opposed to mimicking the default Numpy behavior (e.g., np.mean(arr_2d)).
agg
is an alias for aggregate
. Use the alias.
>>> s = Series(np.random.randn(10))
>>> s.agg('min') -1.3018049988556679
>>> s.agg(['min', 'max']) min -1.301805 max 1.127688 dtype: float64
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http://pandas.pydata.org/pandas-docs/version/0.22.0/generated/pandas.Series.aggregate.html