Let's say I have a dataset (sim_data) with 16 variables, including psychological data (15 items from a questionnaire), and the first column is a categorical variable (country).
I can easily get means/sd by group using:
sim_data.groupby("country").describe()
However, I would like to apply a function (Cronbach's alpha) from a specific package (pip install pingouin) and (import pingouin as pg) with this data and get the results by group (as I did previously). The following code is not working.
pg.cronbach_alpha(sim_data.groupby("country"))
Neither this one
sim_data.groupby('country').apply(lambda grp: pg.cronbach_alpha())
Important notes:
I'm adapting the code from here
That's my routine and dataset if you want to reproduce
import pandas as pd
import numpy as np
import pingouin as pg
from numpy import nan
sim_data = pd.DataFrame.from_dict({'country': {33003: 'Vietnam',
12172: 'Macedonia',
5192: 'Ghana',
32511: 'Vietnam',
7813: 'Ghana',
21440: 'Armenia',
32912: 'Vietnam',
20609: 'Georgia',
7751: 'Ghana',
31228: 'Laos',
36230: 'Serbia',
32025: 'Laos',
21758: 'Armenia',
35730: 'Serbia',
8444: 'Kenya',
19946: 'Georgia',
37532: 'Serbia',
22926: 'Armenia',
27204: 'Sri_Lanka',
31959: 'Laos',
24535: 'Sri_Lanka',
19433: 'Georgia',
17137: 'Ukraine',
26103: 'Sri_Lanka',
33878: 'Vietnam',
39053: 'Philippines',
33799: 'Vietnam',
37183: 'Serbia',
3606: 'Colombia',
2561: 'Colombia',
29960: 'Laos',
32397: 'Vietnam',
39539: 'Philippines',
431: 'Bolivia',
36842: 'Serbia',
16926: 'Ukraine',
9287: 'Kenya',
34246: 'Vietnam',
16277: 'Ukraine',
34105: 'Vietnam',
11032: 'Kenya',
41457: 'Philippines',
34380: 'Vietnam',
19482: 'Georgia',
1844: 'Bolivia',
9552: 'Kenya',
35437: 'Vietnam',
29555: 'Laos',
29993: 'Laos',
28114: 'Yunnan',
15: 'Bolivia',
27712: 'Yunnan',
12313: 'Macedonia',
11631: 'Kenya'},
'step_bfi1_ab_cor': {33003: 1.8333332538604736,
12172: 1.5,
5192: nan,
32511: 1.4166666269302368,
7813: nan,
21440: 2.4166665077209473,
32912: 1.0,
20609: 4.0,
7751: 0.5,
31228: 2.25,
36230: 2.9375,
32025: 1.875,
21758: 3.9166665077209473,
35730: 2.25,
8444: 3.5833334922790527,
19946: 2.3333334922790527,
37532: 4.0625,
22926: 3.5,
27204: 4.083333492279053,
31959: 3.0,
24535: 3.5,
19433: 2.0833334922790527,
17137: 3.25,
26103: 1.1666666269302368,
33878: 1.6666667461395264,
39053: 1.75,
33799: 0.75,
37183: 3.375,
3606: 4.25,
2561: 2.8333334922790527,
29960: 4.25,
32397: 3.8333332538604736,
39539: 2.5625,
431: 3.25,
36842: 3.8125,
16926: 1.9166667461395264,
9287: 2.3333334922790527,
34246: 1.0,
16277: 2.9166667461395264,
34105: 1.5833333730697632,
11032: 1.75,
41457: 3.75,
34380: 1.5833332538604736,
19482: 0.9166666269302368,
1844: 3.6666667461395264,
9552: 2.25,
35437: 1.0833332538604736,
29555: 2.25,
29993: 4.25,
28114: 3.6666665077209473,
15: 3.0,
27712: 3.25,
12313: 2.0833334922790527,
11631: 2.5833334922790527},
'step_bfi3_ab_cor': {33003: 3.8333332538604736,
12172: 3.5,
5192: nan,
32511: 3.4166665077209473,
7813: nan,
21440: 3.4166665077209473,
32912: 3.0,
20609: 4.0,
7751: 2.5,
31228: 4.25,
36230: 3.6875,
32025: 3.875,
21758: 3.9166665077209473,
35730: 2.25,
8444: 4.583333492279053,
19946: 2.3333334922790527,
37532: 2.5625,
22926: 2.5,
27204: 3.0833334922790527,
31959: 4.0,
24535: 2.5,
19433: 3.0833334922790527,
17137: 3.25,
26103: 3.1666665077209473,
33878: 3.6666667461395264,
39053: 2.5,
33799: 3.75,
37183: 3.375,
3606: 4.25,
2561: 2.8333334922790527,
29960: 3.25,
32397: 2.8333332538604736,
39539: 2.5625,
431: 3.25,
36842: 3.0625,
16926: 3.9166667461395264,
9287: 3.3333334922790527,
34246: 4.0,
16277: 1.9166667461395264,
34105: 3.5833334922790527,
11032: 3.75,
41457: 2.25,
34380: 2.5833332538604736,
19482: 3.9166665077209473,
1844: 2.6666667461395264,
9552: 3.25,
35437: 3.0833332538604736,
29555: 2.25,
29993: 2.25,
28114: 3.6666665077209473,
15: 3.0,
27712: 2.25,
12313: 4.083333492279053,
11631: 3.5833334922790527},
'step_bfi5_ab_cor': {33003: 0.8333332538604736,
12172: 0.5,
5192: nan,
32511: 2.4166665077209473,
7813: nan,
21440: 2.4166665077209473,
32912: 2.0,
20609: 2.0,
7751: 0.5,
31228: 3.25,
36230: 3.6875,
32025: 1.875,
21758: 3.9166665077209473,
35730: 2.25,
8444: 1.5833333730697632,
19946: 1.3333333730697632,
37532: 1.8125,
22926: 1.5,
27204: 2.0833334922790527,
31959: 3.0,
24535: 1.5,
19433: 1.0833333730697632,
17137: 2.25,
26103: 4.166666507720947,
33878: 1.6666667461395264,
39053: 1.75,
33799: 1.75,
37183: 3.375,
3606: 2.25,
2561: 1.8333333730697632,
29960: 3.25,
32397: 1.8333332538604736,
39539: 2.5625,
431: 1.25,
36842: 3.8125,
16926: 1.9166667461395264,
9287: 1.3333333730697632,
34246: 3.0,
16277: 1.9166667461395264,
34105: 1.5833333730697632,
11032: 2.75,
41457: 2.25,
34380: 2.5833332538604736,
19482: 1.9166666269302368,
1844: 3.6666667461395264,
9552: 1.25,
35437: 1.0833332538604736,
29555: 1.25,
29993: 3.25,
28114: 2.6666665077209473,
15: 2.0,
27712: 3.25,
12313: 1.0833333730697632,
11631: 3.5833334922790527},
'step_bfi6_ab_cor': {33003: 4.1666669845581055,
12172: 1.5,
5192: nan,
32511: 1.5833333730697632,
7813: nan,
21440: 2.5833334922790527,
32912: 4.0,
20609: 3.0,
7751: 1.5,
31228: 2.75,
36230: 2.8125,
32025: 4.125,
21758: 4.083333492279053,
35730: 1.25,
8444: 3.4166665077209473,
19946: 2.6666665077209473,
37532: 3.9375,
22926: 2.5,
27204: 2.9166665077209473,
31959: 2.0,
24535: 2.5,
19433: 2.9166665077209473,
17137: 2.75,
26103: 0.8333333730697632,
33878: 4.3333330154418945,
39053: 2.5,
33799: 4.25,
37183: 3.125,
3606: 2.75,
2561: 3.1666665077209473,
29960: 3.75,
32397: 1.1666667461395264,
39539: 3.9375,
431: 1.75,
36842: 2.6875,
16926: 2.0833332538604736,
9287: 2.6666665077209473,
34246: 3.0,
16277: 2.0833332538604736,
34105: 2.4166665077209473,
11032: 3.25,
41457: 4.25,
34380: 2.4166667461395264,
19482: 4.083333492279053,
1844: 3.3333332538604736,
9552: 2.75,
35437: 2.9166667461395264,
29555: 1.75,
29993: 2.75,
28114: 3.3333334922790527,
15: 2.0,
27712: 1.75,
12313: 2.9166665077209473,
11631: 3.4166665077209473},
'step_bfi7_ab_cor': {33003: 1.8333332538604736,
12172: 1.5,
5192: nan,
32511: 1.4166666269302368,
7813: nan,
21440: 2.4166665077209473,
32912: 3.0,
20609: 2.0,
7751: 1.5,
31228: 3.25,
36230: 3.6875,
32025: 1.875,
21758: 3.9166665077209473,
35730: 3.75,
8444: 2.5833334922790527,
19946: 1.3333333730697632,
37532: 4.0625,
22926: 2.5,
27204: 3.0833334922790527,
31959: 1.0,
24535: 1.5,
19433: 2.0833334922790527,
17137: 2.25,
26103: 2.1666665077209473,
33878: 2.6666667461395264,
39053: 3.25,
33799: 0.75,
37183: 3.375,
3606: 2.25,
2561: 1.8333333730697632,
29960: 2.25,
32397: 3.8333332538604736,
39539: 4.0625,
431: 3.25,
36842: 3.8125,
16926: 1.9166667461395264,
9287: 2.3333334922790527,
34246: 2.0,
16277: 2.9166667461395264,
34105: 1.5833333730697632,
11032: 1.75,
41457: 3.75,
34380: 2.5833332538604736,
19482: 2.9166665077209473,
1844: 1.6666667461395264,
9552: 2.25,
35437: 2.0833332538604736,
29555: 2.25,
29993: 2.25,
28114: 3.6666665077209473,
15: 3.0,
27712: 1.25,
12313: 4.083333492279053,
11631: 3.5833334922790527},
'step_bfi10_ab_cor': {33003: 3.8333332538604736,
12172: 3.5,
5192: nan,
32511: 3.4166665077209473,
7813: nan,
21440: 3.4166665077209473,
32912: 3.0,
20609: 4.0,
7751: 3.5,
31228: 3.25,
36230: 3.6875,
32025: 1.875,
21758: 3.9166665077209473,
35730: 2.25,
8444: 2.5833334922790527,
19946: 4.333333492279053,
37532: 2.5625,
22926: 2.5,
27204: 4.083333492279053,
31959: 2.0,
24535: 0.4999999403953552,
19433: 3.0833334922790527,
17137: 3.25,
26103: 3.1666665077209473,
33878: 2.6666667461395264,
39053: 3.25,
33799: 1.75,
37183: 3.375,
3606: 2.25,
2561: 2.8333334922790527,
29960: 2.25,
32397: 1.8333332538604736,
39539: 4.0625,
431: 3.25,
36842: 3.0625,
16926: 3.9166667461395264,
9287: 2.3333334922790527,
34246: 4.0,
16277: 2.9166667461395264,
34105: 2.5833334922790527,
11032: 3.75,
41457: 2.25,
34380: 3.5833332538604736,
19482: 3.9166665077209473,
1844: 3.6666667461395264,
9552: 3.25,
35437: 3.0833332538604736,
29555: 2.25,
29993: 2.25,
28114: 3.6666665077209473,
15: 3.0,
27712: 3.25,
12313: 2.0833334922790527,
11631: 4.583333492279053},
'step_bfi17_ab_cor': {33003: 2.8333332538604736,
12172: 1.5,
5192: nan,
32511: 3.4166665077209473,
7813: nan,
21440: 1.4166666269302368,
32912: 2.0,
20609: 1.0,
7751: 3.5,
31228: 3.25,
36230: 2.1875,
32025: nan,
21758: 3.9166665077209473,
35730: 3.75,
8444: 3.5833334922790527,
19946: 2.3333334922790527,
37532: 2.5625,
22926: 2.5,
27204: 3.0833334922790527,
31959: 3.0,
24535: 2.5,
19433: 4.083333492279053,
17137: 2.25,
26103: 2.1666665077209473,
33878: 2.6666667461395264,
39053: 1.75,
33799: 2.75,
37183: 3.375,
3606: 4.25,
2561: 0.8333333730697632,
29960: 3.25,
32397: 1.8333332538604736,
39539: 2.5625,
431: 1.25,
36842: 2.3125,
16926: 2.9166667461395264,
9287: 3.3333334922790527,
34246: 2.0,
16277: 2.9166667461395264,
34105: 3.5833334922790527,
11032: 2.75,
41457: 3.75,
34380: 2.5833332538604736,
19482: 3.9166665077209473,
1844: 3.6666667461395264,
9552: 3.25,
35437: 2.0833332538604736,
29555: 2.25,
29993: 2.25,
28114: 3.6666665077209473,
15: 3.0,
27712: 2.25,
12313: 3.0833334922790527,
11631: 3.5833334922790527},
'step_bfi19_ab_cor': {33003: 3.1666667461395264,
12172: 1.5,
5192: nan,
32511: 1.5833333730697632,
7813: nan,
21440: 2.5833334922790527,
32912: 2.0,
20609: 1.0,
7751: 1.5,
31228: 2.75,
36230: 2.0625,
32025: 2.125,
21758: 1.0833333730697632,
35730: 4.25,
8444: 3.4166665077209473,
19946: 3.6666665077209473,
37532: 0.9375,
22926: 2.5,
27204: 2.9166665077209473,
31959: 3.0,
24535: 1.5,
19433: 2.9166665077209473,
17137: 2.75,
26103: 1.8333333730697632,
33878: 3.3333332538604736,
39053: 3.25,
33799: 3.25,
37183: 3.125,
3606: 2.75,
2561: 3.1666665077209473,
29960: 1.75,
32397: 3.1666667461395264,
39539: 2.4375,
431: 1.75,
36842: 2.6875,
16926: 3.0833332538604736,
9287: 4.666666507720947,
34246: 3.0,
16277: 2.0833332538604736,
34105: 3.4166665077209473,
11032: 3.25,
41457: 2.75,
34380: 2.4166667461395264,
19482: 3.0833334922790527,
1844: 4.3333330154418945,
9552: 2.75,
35437: 2.9166667461395264,
29555: 1.75,
29993: 1.75,
28114: 3.3333334922790527,
15: 2.0,
27712: 2.75,
12313: 0.9166666269302368,
11631: 2.4166665077209473},
'step_bfi23_ab_cor': {33003: 1.1666667461395264,
12172: 3.5,
5192: nan,
32511: 4.583333492279053,
7813: nan,
21440: 3.5833334922790527,
32912: 2.0,
20609: 4.0,
7751: 4.5,
31228: 2.75,
36230: 3.5625,
32025: nan,
21758: 4.083333492279053,
35730: 4.25,
8444: 3.4166665077209473,
19946: 3.6666665077209473,
37532: 3.9375,
22926: 3.5,
27204: 2.9166665077209473,
31959: 3.0,
24535: 2.5,
19433: 2.9166665077209473,
17137: 2.75,
26103: 3.8333334922790527,
33878: 1.3333332538604736,
39053: 1.75,
33799: 2.25,
37183: 4.625,
3606: 2.75,
2561: 3.1666665077209473,
29960: 2.75,
32397: 3.1666667461395264,
39539: 2.4375,
431: 3.75,
36842: 3.4375,
16926: 3.0833332538604736,
9287: 1.6666666269302368,
34246: 3.0,
16277: 3.0833332538604736,
34105: 1.4166666269302368,
11032: 4.25,
41457: 2.75,
34380: 2.4166667461395264,
19482: 4.083333492279053,
1844: 3.3333332538604736,
9552: 3.75,
35437: 1.9166667461395264,
29555: 2.75,
29993: 2.75,
28114: 3.3333334922790527,
15: 4.0,
27712: 2.75,
12313: 2.9166665077209473,
11631: 3.4166665077209473},
'step_bfi30_ab_cor': {33003: 1.8333332538604736,
12172: 3.5,
5192: nan,
32511: 2.4166665077209473,
7813: nan,
21440: 3.4166665077209473,
32912: 4.0,
20609: 4.0,
7751: 3.5,
31228: 3.25,
36230: 3.6875,
32025: 1.875,
21758: 3.9166665077209473,
35730: 2.25,
8444: 2.5833334922790527,
19946: 4.333333492279053,
37532: 4.0625,
22926: 3.5,
27204: 4.083333492279053,
31959: 4.0,
24535: 3.5,
19433: 4.083333492279053,
17137: 3.25,
26103: 3.1666665077209473,
33878: 3.6666667461395264,
39053: 1.0,
33799: 0.75,
37183: 3.375,
3606: 4.25,
2561: 2.8333334922790527,
29960: 3.25,
32397: 2.8333332538604736,
39539: 4.0625,
431: 3.25,
36842: 3.8125,
16926: 2.9166667461395264,
9287: 2.3333334922790527,
34246: 3.0,
16277: 2.9166667461395264,
34105: 2.5833334922790527,
11032: 3.75,
41457: 3.75,
34380: 3.5833332538604736,
19482: 3.9166665077209473,
1844: 3.6666667461395264,
9552: 2.25,
35437: 3.0833332538604736,
29555: 2.25,
29993: 3.25,
28114: 3.6666665077209473,
15: 1.0,
27712: 3.25,
12313: 4.083333492279053,
11631: 4.583333492279053},
'step_bfi32_ab_cor': {33003: 3.8333332538604736,
12172: 1.5,
5192: nan,
32511: 3.4166665077209473,
7813: nan,
21440: 3.4166665077209473,
32912: 4.0,
20609: 4.0,
7751: 3.5,
31228: 3.25,
36230: 2.9375,
32025: 2.875,
21758: 3.9166665077209473,
35730: 2.25,
8444: 3.5833334922790527,
19946: 4.333333492279053,
37532: 3.3125,
22926: 3.5,
27204: 4.083333492279053,
31959: 3.0,
24535: 2.5,
19433: 4.083333492279053,
17137: 3.25,
26103: 3.1666665077209473,
33878: 3.6666667461395264,
39053: 1.75,
33799: 3.75,
37183: 1.875,
3606: 4.25,
2561: 2.8333334922790527,
29960: 3.25,
32397: 2.8333332538604736,
39539: 2.5625,
431: 3.25,
36842: 3.0625,
16926: 2.9166667461395264,
9287: 2.3333334922790527,
34246: 4.0,
16277: 2.9166667461395264,
34105: 3.5833334922790527,
11032: 3.75,
41457: 2.25,
34380: 2.5833332538604736,
19482: 3.9166665077209473,
1844: 3.6666667461395264,
9552: 3.25,
35437: 3.0833332538604736,
29555: 3.25,
29993: 3.25,
28114: 3.6666665077209473,
15: 3.0,
27712: 2.25,
12313: 3.0833334922790527,
11631: 3.5833334922790527},
'step_bfi33_ab_cor': {33003: 1.8333332538604736,
12172: 3.5,
5192: nan,
32511: 3.4166665077209473,
7813: nan,
21440: 2.4166665077209473,
32912: 4.0,
20609: 2.0,
7751: 3.5,
31228: 3.25,
36230: 2.9375,
32025: 3.875,
21758: 3.9166665077209473,
35730: 3.75,
8444: 3.5833334922790527,
19946: 4.333333492279053,
37532: 4.0625,
22926: 2.5,
27204: 3.0833334922790527,
31959: 2.0,
24535: 1.5,
19433: 2.0833334922790527,
17137: 1.25,
26103: 3.1666665077209473,
33878: 3.6666667461395264,
39053: 2.5,
33799: 3.75,
37183: 3.375,
3606: 2.25,
2561: 2.8333334922790527,
29960: 3.25,
32397: 2.8333332538604736,
39539: 3.3125,
431: 2.25,
36842: 3.0625,
16926: 2.9166667461395264,
9287: 3.3333334922790527,
34246: 3.0,
16277: 2.9166667461395264,
34105: 3.5833334922790527,
11032: 3.75,
41457: 3.75,
34380: 3.5833332538604736,
19482: 3.9166665077209473,
1844: 3.6666667461395264,
9552: 2.25,
35437: 3.0833332538604736,
29555: 3.25,
29993: 2.25,
28114: 3.6666665077209473,
15: 3.0,
27712: 1.25,
12313: 3.0833334922790527,
11631: 3.5833334922790527},
'step_bfi34_ab_cor': {33003: 3.8333332538604736,
12172: 1.5,
5192: nan,
32511: 3.4166665077209473,
7813: nan,
21440: 3.4166665077209473,
32912: 3.0,
20609: 1.0,
7751: 3.5,
31228: 2.25,
36230: 2.9375,
32025: nan,
21758: 3.9166665077209473,
35730: 3.75,
8444: 2.5833334922790527,
19946: 3.3333334922790527,
37532: 2.5625,
22926: 2.5,
27204: 2.0833334922790527,
31959: 2.0,
24535: 1.5,
19433: 3.0833334922790527,
17137: 3.25,
26103: 2.1666665077209473,
33878: 2.6666667461395264,
39053: 2.5,
33799: 3.75,
37183: 3.375,
3606: 1.25,
2561: 3.8333334922790527,
29960: 2.25,
32397: 1.8333332538604736,
39539: 2.5625,
431: 2.25,
36842: 2.3125,
16926: 2.9166667461395264,
9287: 3.3333334922790527,
34246: 4.0,
16277: 2.9166667461395264,
34105: 1.5833333730697632,
11032: 3.75,
41457: 2.25,
34380: 1.5833332538604736,
19482: 3.9166665077209473,
1844: 3.6666667461395264,
9552: 3.25,
35437: 3.0833332538604736,
29555: 2.25,
29993: 2.25,
28114: 2.6666665077209473,
15: 3.0,
27712: 2.25,
12313: 1.0833333730697632,
11631: 2.5833334922790527},
'step_bfi36_ab_cor': {33003: 2.8333332538604736,
12172: 3.5,
5192: nan,
32511: 3.4166665077209473,
7813: nan,
21440: 2.4166665077209473,
32912: 3.0,
20609: 4.0,
7751: 2.5,
31228: 3.25,
36230: 3.6875,
32025: 1.875,
21758: 1.9166666269302368,
35730: 2.25,
8444: 3.5833334922790527,
19946: 4.333333492279053,
37532: 3.3125,
22926: 3.5,
27204: 3.0833334922790527,
31959: 3.0,
24535: 2.5,
19433: 4.083333492279053,
17137: 2.25,
26103: 2.1666665077209473,
33878: 3.6666667461395264,
39053: 3.25,
33799: 3.75,
37183: 3.375,
3606: 4.25,
2561: 2.8333334922790527,
29960: 3.25,
32397: 1.8333332538604736,
39539: 2.5625,
431: 2.25,
36842: 3.0625,
16926: 1.9166667461395264,
9287: 0.3333333730697632,
34246: 2.0,
16277: 2.9166667461395264,
34105: 3.5833334922790527,
11032: 3.75,
41457: 3.75,
34380: 3.5833332538604736,
19482: 3.9166665077209473,
1844: 3.6666667461395264,
9552: 3.25,
35437: 3.0833332538604736,
29555: 1.25,
29993: 2.25,
28114: 3.6666665077209473,
15: 3.0,
27712: 3.25,
12313: 4.083333492279053,
11631: 3.5833334922790527},
'step_bfi39_ab_cor': {33003: 4.1666669845581055,
12172: 3.5,
5192: nan,
32511: 4.583333492279053,
7813: nan,
21440: 2.5833334922790527,
32912: 3.0,
20609: 1.0,
7751: 2.5,
31228: 3.75,
36230: 4.3125,
32025: 1.125,
21758: 4.083333492279053,
35730: 2.75,
8444: 3.4166665077209473,
19946: 3.6666665077209473,
37532: 2.4375,
22926: 2.5,
27204: 2.9166665077209473,
31959: 3.0,
24535: 1.5,
19433: 2.9166665077209473,
17137: 2.75,
26103: 2.8333334922790527,
33878: 3.3333332538604736,
39053: 3.25,
33799: 3.25,
37183: 1.625,
3606: 3.75,
2561: 3.1666665077209473,
29960: 3.75,
32397: 3.1666667461395264,
39539: 0.9375,
431: 2.75,
36842: 2.6875,
16926: 3.0833332538604736,
9287: 2.6666665077209473,
34246: 3.0,
16277: 4.0833330154418945,
34105: 4.416666507720947,
11032: 2.25,
41457: 1.25,
34380: 2.4166667461395264,
19482: 1.0833333730697632,
1844: 3.3333332538604736,
9552: 1.75,
35437: 3.9166667461395264,
29555: 2.75,
29993: 2.75,
28114: 3.3333334922790527,
15: 4.0,
27712: 2.75,
12313: 2.9166665077209473,
11631: 2.4166665077209473}})
I'm a heavy R user and and I'm translating the following code to python
sim_data %>%
select('step_bfi1_ab_cor':'step_bfi39_ab_cor', "country") %>%
nest(-country) %>%
mutate(result=map(data, ~psych::alpha(.)$total)) %>%
select(country,result) %>%
unnest()
Suggestions are welcome. Please let me know if there's another way (more elegant) to solve my problem. Thank you
Usually, base R (not tidy R) is easier to translate to Python Pandas. What your R code appears to be doing is subsetting the dataframe by country column and running each subset into psych::alpha(). Then extracted statistics are returned into a data frame with country indicator.
You can do the exact same with base R's by which can translate into Pandas' groupby in a list comprehension. It looks like psych::alpha returns more statistics than pingouin.cronbach_alpha. Adjust fields and return values below as needed in untested code.
Base R (using docs)
# DEFINE METHOD
run_cronbach_alpha <- function(sub) {
results <- psych::alpha(sub)$total # RETURNS LIST
data.frame(country = sub$country[1],
raw_alpha = results$raw_alpha,
std.alpha = results$std.alpha,
G6 = results$G6,
average_r = results$average_r,
median_r = results$median,
mean = results$mean,
sd = results$sd)
}
# FILTER COLUMNS IN DATA FRAME
sim_short <- sim_data[c("step_bfi1_ab_cor", ..., "step_bfi39_ab_cor", "country")]
# RUN METHOD BY COUNTRY SUBSETS TO RETURN DF LIST
results_df_list <- by(sim_short, sim_short$country, run_cronbach_alpha)
# ROW BIND ALL DFs TO SINGLE FINAL DATA FRAME
results_df <- do.call(rbind.data.frame, results_df_list)
Python Pandas (using docs)
# DEFINE METHOD
def run_cronbach_alpha(c, sub):
results = pg.cronbach_alpha(sub.drop(["country"], axis="columns")) # RETURNS TUPLE
return pd.DataFrame({'country': c, 'cronbach_alpha': results[0], index=[0]})
# FILTER COLUMNS IN DATA FRAME
sim_short = sim_data.reindex(["step_bfi1_ab_cor", ..., "step_bfi39_ab_cor", "country"],
axis='columns')
# RUN METHOD BY COUNTRY SUBSETS TO RETURN DF LIST
results_df_list = [run_cronbach_alpha(i, df) for i,df in sim_short.groupby("country")]
# CONCATENATE ALL DFs TO SINGLE FINAL DATA FRAME
results_df = pd.concat(results_df_list)