with_groups

In [1]:

# https://dplyr.tidyverse.org/reference/with_groups.html
%run nb_helpers.py

from datar.all import *

nb_header(with_groups)

# https://dplyr.tidyverse.org/reference/with_groups.html %run nb_helpers.py from datar.all import * nb_header(with_groups)

Try this notebook on binder.

★ with_groups

¶

Modify the grouping variables for a single operation.¶

Args:¶

  _data: A data frame
  _groups: columns passed by group_by
    Use None to temporarily ungroup.

  _func: Function to apply to regrouped data.

Returns:¶

  The new data frame with operations applied.

In [2]:

df = tibble(g=c(1, 1, 2, 2, 3), x=runif(5))
df >> with_groups(f.g, mutate, x_mean = mean(f.x))

df = tibble(g=c(1, 1, 2, 2, 3), x=runif(5)) df >> with_groups(f.g, mutate, x_mean = mean(f.x))

Out[2]:

	g	x	x_mean
	<int64>	<float64>	<float64>
0	1	0.244611	0.525006
1	1	0.805402	0.525006
2	2	0.862707	0.829213
3	2	0.795719	0.829213
4	3	0.812910	0.812910

TibbleGrouped: g (n=3)

In [3]:

df >> with_groups(f.g, lambda df: df >> mutate(x1 = first(f.x)))

df >> with_groups(f.g, lambda df: df >> mutate(x1 = first(f.x)))

Out[3]:

	g	x	x1
	<int64>	<float64>	<float64>
0	1	0.244611	0.244611
1	1	0.805402	0.244611
2	2	0.862707	0.862707
3	2	0.795719	0.862707
4	3	0.812910	0.812910

TibbleGrouped: g (n=3)

In [4]:

df >> \
  group_by(f.g) >> \
  with_groups(None, mutate, x_mean = mean(f.x))

df >> \ group_by(f.g) >> \ with_groups(None, mutate, x_mean = mean(f.x))

Out[4]:

	g	x	x_mean
	<int64>	<float64>	<float64>
0	1	0.244611	0.70427
1	1	0.805402	0.70427
2	2	0.862707	0.70427
3	2	0.795719	0.70427
4	3	0.812910	0.70427

In [5]:

df >> \
  group_by(f.g) >> \
  with_groups(None, mutate, g=None)

df >> \ group_by(f.g) >> \ with_groups(None, mutate, g=None)

Out[5]:

	x
	<float64>
0	0.244611
1	0.805402
2	0.862707
3	0.795719
4	0.812910