pynapple.IntervalSet.groupby

IntervalSet.groupby(by, get_group=None)

Group pynapple object by metadata name(s).

Parameters:

• by (str or list of str) – Metadata name(s) to group by.

• get_group (dictionary key, optional) – Name of the group to return.

Returns:

Dictionary of object indices (dictionary values) corresponding to each group (dictionary keys), or pynapple object corresponding to ‘get_group’ if it has been supplied.

Return type:

dict or pynapple object

Raises:

ValueError – If metadata name does not exist.

Examples

>>> import pynapple as nap
>>> import numpy as np
>>> times = np.array([[0, 5], [10, 12], [20, 33]])
>>> metadata = {"l1": [1, 2, 2], "l2": ["x", "x", "y"]}
>>> ep = nap.IntervalSet(times,metadata=metadata)
>>> print(ep)
  index    start    end    l1  l2
      0        0      5     1  x
      1       10     12     2  x
      2       20     33     2  y
shape: (3, 2), time unit: sec.

Grouping by a single column:

>>> ep.groupby("l2")
{'x': [0, 1], 'y': [2]}

Grouping by multiple columns:

>>> ep.groupby(["l1","l2"])
{(1, 'x'): [0], (2, 'x'): [1], (2, 'y'): [2]}

Filtering to a specific group using the output dictionary:

>>> groups = ep.groupby("l2")
>>> ep[groups["x"]]
  index    start    end    l1  l2
      0        0      5     1  x
      1       10     12     2  x
shape: (2, 2), time unit: sec.

Filtering to a specific group using the get_group argument:

>>> ep.groupby("l2", get_group="x")
  index    start    end    l1  l2
      0        0      5     1  x
      1       10     12     2  x
shape: (2, 2), time unit: sec.