GroupBy # pandas.api.typing.DataFrameGroupBy and pandas.api.typing.SeriesGroupBy instances are returned by groupby calls pandas.DataFrame.groupby() and pandas.Series.groupby() respectively.
A groupby operation involves some combination of splitting the object, applying a function, and combining the results. This can be used to group large amounts of data and compute operations on these groups.
itertools.groupby(iterable, key=None) ¶ Make an iterator that returns consecutive keys and groups from the iterable. The key is a function computing a key value for each element. If not specified or is None, key defaults to an identity function and returns the element unchanged.
Contenido: 00:00 Introducción 02:19 Organización del tutorial 02:50 El set de datos 06:16 ¿Qué es y cuándo usar el agrupamiento de datos? 09:02 Uso básico de “groupby” en Pandas 20:02 ...
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By “groupby” we are referring to a process involving one or more of the following steps: Splitting the data into groups based on some criteria. Applying a function to each group independently. Combining the results into a data structure. Out of these, the split step is the most straightforward.
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