6 examples of 'pandas groupby iterate' in Python

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def _iter_groups(self, df, y=None):
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    """Iterate over groups of `df`, and, if provided, matching labels."""
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    groups = df.groupby(self.groupby).indices
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    for key, sub_idx in groups.items():
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        sub_df = df.iloc[sub_idx]
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        sub_y = y[sub_idx] if y is not None else None
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        yield key, sub_df, sub_y

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def groupby(xs, keys):
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    result = defaultdict(list)
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    for (x, key) in zip(xs, keys):
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        result[key].append(x)
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    return result

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def __getitem__(self, index):
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    return StreamingSeriesGroupby(self.root, self.grouper, index)

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def __iter__(self):
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    return iteraggregate(self.source, self.key, self.aggregators, self.errorvalue)

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def groupby_deco(func):
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    def func_wrapper(self, thing, *args, **kwargs):
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        if isinstance(thing, pd.core.groupby.DataFrameGroupBy):
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            agg = thing.apply(lambda x: func(self, x, *args, **kwargs))
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            is_series = isinstance(agg, pd.core.series.Series)
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            has_multiindex = isinstance(agg.index, pd.MultiIndex)
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            if is_series and has_multiindex:
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                return agg.unstack()
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            else:
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                return agg
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        return func(self, thing, *args, **kwargs)
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    return func_wrapper

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def group_by(collection, iteratee=None):
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    """Creates an object composed of keys generated from the results of running
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    each element of a `collection` through the iteratee.
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    Args:
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        collection (list|dict): Collection to iterate over.
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        iteratee (mixed, optional): Iteratee applied per iteration.
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    Returns:
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        dict: Results of grouping by `iteratee`.
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    Example:
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        >>> results = group_by([{'a': 1, 'b': 2}, {'a': 3, 'b': 4}], 'a')
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        >>> assert results == {1: [{'a': 1, 'b': 2}], 3: [{'a': 3, 'b': 4}]}
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        >>> results = group_by([{'a': 1, 'b': 2}, {'a': 3, 'b': 4}], {'a': 1})
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        >>> assert results == {False: [{'a': 3, 'b': 4}],\
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                               True: [{'a': 1, 'b': 2}]}
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    .. versionadded:: 1.0.0
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    """
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    ret = {}
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    cbk = pyd.iteratee(iteratee)
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    for value in collection:
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        key = cbk(value)
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        ret.setdefault(key, [])
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        ret[key].append(value)
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    return ret