fastgrouper

Allows for fast groupby-apply operations, in python.

Install

Users can install the package from PyPI via:

python -m pip install fastgrouper

Usage

Use the arr interface, for numpy array focused applications.

import numpy as np
import fastgrouper.arr
  
def baz(x, y):
    return np.mean(x + y) - 3

# Sample arrays, to slice
xvals = np.array([1, 2, 10])
yvals = np.array([4, 5, 6])
  
# Group ids
gids  = np.array([1, -3, 1])

# Perform groupby-apply; note that keyword args are supported as well.
grpd = fastgrouper.arr.Grouped(gids)
result = grpd.apply(baz, xvals, y=yvals) # np.array([7.5, 4])

# The gids correponding to the result above can be found via the `dedup_gids` attribute.
grpd.dedup_gids # np.array([ 1, -3])

# Users can also perform groupby-apply, and then expand results back to align with the original gids.
result = grpd.apply_expand(baz, xvals, yvals) # np.array([7.5, 4, 7.5])

The li interface returns the results over the groups as a list (instead of an array); this may be useful for functions that return different-sized results. Note that in all interfaces (e.g. both arr and li), the order in which the group elements appear is preserved when the group slices are passed to the function being applied.

import numpy as np
import fastgrouper.li
  
def bop(x):
    return list(x)

# Sample arrays, to slice
xvals = np.array([2, 3, 4])
  
# Group ids
gids  = np.array([10, -20, 10])

grpd = fastgrouper.li.Grouped(gids)
grpd.apply(bop, xvals) # [[2, 4], [3]]

For additional examples, checkout the tests.