Nothing
tests/testthat/_snaps/stat.md
In baizer: Useful Functions for Data Processing
stat_test, by
Code
stat_test(mini_diamond, y = price, x = cut, .by = clarity) %>% print(width = Inf,
n = Inf)
Output
# A tibble: 24 x 9
y clarity group1 group2 n1 n2 p plim psymbol
<chr> <chr> <chr> <chr> <int> <int> <chr> <dbl> <chr>
1 price I1 Fair Good 5 5 0.31 1.01 NS
2 price I1 Fair Ideal 5 4 0.90 1.01 NS
3 price I1 Good Ideal 5 4 0.19 1.01 NS
4 price IF Fair Good 4 5 0.063 1.01 NS
5 price IF Fair Ideal 4 4 0.059 1.01 NS
6 price IF Good Ideal 5 4 1.0 1.01 NS
7 price SI1 Fair Good 5 4 1.0 1.01 NS
8 price SI1 Fair Ideal 5 5 1.0 1.01 NS
9 price SI1 Good Ideal 4 5 0.41 1.01 NS
10 price SI2 Fair Good 4 4 0.057 1.01 NS
11 price SI2 Fair Ideal 4 4 0.057 1.01 NS
12 price SI2 Good Ideal 4 4 0.69 1.01 NS
13 price VS1 Fair Good 3 2 0.20 1.01 NS
14 price VS1 Fair Ideal 3 5 0.036 0.05 *
15 price VS1 Good Ideal 2 5 0.57 1.01 NS
16 price VS2 Fair Good 5 4 0.41 1.01 NS
17 price VS2 Fair Ideal 5 2 0.86 1.01 NS
18 price VS2 Good Ideal 4 2 0.80 1.01 NS
19 price VVS1 Fair Good 5 4 0.90 1.01 NS
20 price VVS1 Fair Ideal 5 5 0.15 1.01 NS
21 price VVS1 Good Ideal 4 5 0.19 1.01 NS
22 price VVS2 Fair Good 4 3 0.63 1.01 NS
23 price VVS2 Fair Ideal 4 5 0.032 0.05 *
24 price VVS2 Good Ideal 3 5 0.071 1.01 NS
stat_test
Code
stat_test(mini_diamond, y = price, x = cut) %>% print(width = Inf, n = Inf)
Output
# A tibble: 3 x 8
y group1 group2 n1 n2 p plim psymbol
<chr> <chr> <chr> <int> <int> <chr> <dbl> <chr>
1 price Fair Good 35 31 0.041 0.05 *
2 price Fair Ideal 35 34 0.018 0.05 *
3 price Good Ideal 31 34 0.93 1.01 NS
stat_test, exclude_func
Code
stat_test(df, x = coord, y = value, paired = TRUE, paired_by = id,
exclude_func = ~ abs(.x - .y) < 0.1)
Output
exclude 92 data pair because of exclude_func
# A tibble: 1 x 8
y group1 group2 n1 n2 p plim psymbol
<chr> <chr> <chr> <int> <int> <chr> <dbl> <chr>
1 value x y 100 100 0.0078 0.01 **
stat_test, one side NA
Code
stat_test(df, x = type, y = value, .by = cut, paired = TRUE, paired_by = id)
Output
# A tibble: 2 x 9
y cut group1 group2 n1 n2 p plim psymbol
<chr> <chr> <chr> <chr> <int> <int> <chr> <dbl> <chr>
1 value Good x y 31 31 0.65 1.01 NS
2 value Ideal x y 34 34 0.047 0.05 *
stat_fc
Code
stat_fc(mini_diamond, y = price, x = cut, .by = clarity) %>% print(n = Inf)
Output
# A tibble: 24 x 8
y clarity group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 price I1 Fair Good 4695. 2760. 1.70 1.7x
2 price I1 Fair Ideal 4695. 4249 1.11 1.1x
3 price I1 Good Ideal 2760. 4249 0.649 0.65x
4 price IF Fair Good 2016 1044. 1.93 1.9x
5 price IF Fair Ideal 2016 962. 2.10 2.1x
6 price IF Good Ideal 1044. 962. 1.09 1.1x
7 price SI1 Fair Good 5844. 3227. 1.81 1.8x
8 price SI1 Fair Ideal 5844. 3877. 1.51 1.5x
9 price SI1 Good Ideal 3227. 3877. 0.832 0.83x
10 price SI2 Fair Good 13162. 6539. 2.01 2.0x
11 price SI2 Fair Ideal 13162. 4267. 3.08 3.1x
12 price SI2 Good Ideal 6539. 4267. 1.53 1.5x
13 price VS1 Fair Good 6228. 775 8.04 8.0x
14 price VS1 Fair Ideal 6228. 2256. 2.76 2.8x
15 price VS1 Good Ideal 775 2256. 0.343 0.34x
16 price VS2 Fair Good 3529. 5582. 0.632 0.63x
17 price VS2 Fair Ideal 3529. 3024. 1.17 1.2x
18 price VS2 Good Ideal 5582. 3024. 1.85 1.8x
19 price VVS1 Fair Good 2184 2810. 0.777 0.78x
20 price VVS1 Fair Ideal 2184 4652. 0.469 0.47x
21 price VVS1 Good Ideal 2810. 4652. 0.604 0.60x
22 price VVS2 Fair Good 3543 7481. 0.474 0.47x
23 price VVS2 Fair Ideal 3543 1072. 3.31 3.3x
24 price VVS2 Good Ideal 7481. 1072. 6.98 7.0x
stat_fc, rev_div=TRUE
Code
stat_fc(mini_diamond, y = price, x = cut, rev_div = TRUE, .by = clarity) %>%
print(n = Inf)
Output
# A tibble: 24 x 8
y clarity group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 price I1 Fair Good 4695. 2760. 0.588 0.59x
2 price I1 Fair Ideal 4695. 4249 0.905 0.90x
3 price I1 Good Ideal 2760. 4249 1.54 1.5x
4 price IF Fair Good 2016 1044. 0.518 0.52x
5 price IF Fair Ideal 2016 962. 0.477 0.48x
6 price IF Good Ideal 1044. 962. 0.921 0.92x
7 price SI1 Fair Good 5844. 3227. 0.552 0.55x
8 price SI1 Fair Ideal 5844. 3877. 0.663 0.66x
9 price SI1 Good Ideal 3227. 3877. 1.20 1.2x
10 price SI2 Fair Good 13162. 6539. 0.497 0.50x
11 price SI2 Fair Ideal 13162. 4267. 0.324 0.32x
12 price SI2 Good Ideal 6539. 4267. 0.653 0.65x
13 price VS1 Fair Good 6228. 775 0.124 0.12x
14 price VS1 Fair Ideal 6228. 2256. 0.362 0.36x
15 price VS1 Good Ideal 775 2256. 2.91 2.9x
16 price VS2 Fair Good 3529. 5582. 1.58 1.6x
17 price VS2 Fair Ideal 3529. 3024. 0.857 0.86x
18 price VS2 Good Ideal 5582. 3024. 0.542 0.54x
19 price VVS1 Fair Good 2184 2810. 1.29 1.3x
20 price VVS1 Fair Ideal 2184 4652. 2.13 2.1x
21 price VVS1 Good Ideal 2810. 4652. 1.66 1.7x
22 price VVS2 Fair Good 3543 7481. 2.11 2.1x
23 price VVS2 Fair Ideal 3543 1072. 0.303 0.30x
24 price VVS2 Good Ideal 7481. 1072. 0.143 0.14x
stat_fc, method='median'
Code
suppressWarnings(stat_fc(mini_diamond, y = price, x = cut, .by = clarity,
method = "median") %>% print(n = Inf))
Output
# A tibble: 24 x 8
y clarity group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 price I1 Fair Good 5667 2143 2.64 2.6x
2 price I1 Fair Ideal 5667 3024 1.87 1.9x
3 price I1 Good Ideal 2143 3024 0.709 0.71x
4 price IF Fair Good 1826. 1052 1.74 1.7x
5 price IF Fair Ideal 1826. 877 2.08 2.1x
6 price IF Good Ideal 1052 877 1.20 1.2x
7 price SI1 Fair Good 3027 3533 0.857 0.86x
8 price SI1 Fair Ideal 3027 5370 0.564 0.56x
9 price SI1 Good Ideal 3533 5370 0.658 0.66x
10 price SI2 Fair Good 14716. 5671 2.59 2.6x
11 price SI2 Fair Ideal 14716. 3086. 4.77 4.8x
12 price SI2 Good Ideal 5671 3086. 1.84 1.8x
13 price VS1 Fair Good 6115 775 7.89 7.9x
14 price VS1 Fair Ideal 6115 2498 2.45 2.4x
15 price VS1 Good Ideal 775 2498 0.310 0.31x
16 price VS2 Fair Good 2815 3746. 0.751 0.75x
17 price VS2 Fair Ideal 2815 3024. 0.931 0.93x
18 price VS2 Good Ideal 3746. 3024. 1.24 1.2x
19 price VVS1 Fair Good 1691 1314 1.29 1.3x
20 price VVS1 Fair Ideal 1691 3487 0.485 0.48x
21 price VVS1 Good Ideal 1314 3487 0.377 0.38x
22 price VVS2 Fair Good 3800 6748 0.563 0.56x
23 price VVS2 Fair Ideal 3800 854 4.45 4.4x
24 price VVS2 Good Ideal 6748 854 7.90 7.9x
stat_fc, method='geom_mean'
Code
stat_fc(mini_diamond, y = price, x = cut, .by = clarity, method = "geom_mean") %>%
print(n = Inf)
Output
# A tibble: 24 x 8
y clarity group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 price I1 Fair Good 3911. 1571. 2.49 2.5x
2 price I1 Fair Ideal 3911. 3611. 1.08 1.1x
3 price I1 Good Ideal 1571. 3611. 0.435 0.44x
4 price IF Fair Good 1874. 961. 1.95 1.9x
5 price IF Fair Ideal 1874. 950. 1.97 2.0x
6 price IF Good Ideal 961. 950. 1.01 1.0x
7 price SI1 Fair Good 3833. 2401. 1.60 1.6x
8 price SI1 Fair Ideal 3833. 3268. 1.17 1.2x
9 price SI1 Good Ideal 2401. 3268. 0.735 0.73x
10 price SI2 Fair Good 12609. 4605. 2.74 2.7x
11 price SI2 Fair Ideal 12609. 3319. 3.80 3.8x
12 price SI2 Good Ideal 4605. 3319. 1.39 1.4x
13 price VS1 Fair Good 6194. 754. 8.21 8.2x
14 price VS1 Fair Ideal 6194. 1641. 3.77 3.8x
15 price VS1 Good Ideal 754. 1641. 0.459 0.46x
16 price VS2 Fair Good 3330. 4728. 0.704 0.70x
17 price VS2 Fair Ideal 3330. 1845. 1.80 1.8x
18 price VS2 Good Ideal 4728. 1845. 2.56 2.6x
19 price VVS1 Fair Good 1863. 1773. 1.05 1.1x
20 price VVS1 Fair Ideal 1863. 4052. 0.460 0.46x
21 price VVS1 Good Ideal 1773. 4052. 0.438 0.44x
22 price VVS2 Fair Good 3184. 4688. 0.679 0.68x
23 price VVS2 Fair Ideal 3184. 967. 3.29 3.3x
24 price VVS2 Good Ideal 4688. 967. 4.85 4.8x
stat_fc, one side NA
Code
stat_fc(df, x = type, y = value, .by = cut)
Output
# A tibble: 2 x 8
y cut group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 value Good x y 5.65 5.65 0.999 1.00x
2 value Ideal x y 5.57 5.59 0.997 1.00x
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stat_test, by
Code
stat_test(mini_diamond, y = price, x = cut, .by = clarity) %>% print(width = Inf,
n = Inf)
Output
# A tibble: 24 x 9
y clarity group1 group2 n1 n2 p plim psymbol
<chr> <chr> <chr> <chr> <int> <int> <chr> <dbl> <chr>
1 price I1 Fair Good 5 5 0.31 1.01 NS
2 price I1 Fair Ideal 5 4 0.90 1.01 NS
3 price I1 Good Ideal 5 4 0.19 1.01 NS
4 price IF Fair Good 4 5 0.063 1.01 NS
5 price IF Fair Ideal 4 4 0.059 1.01 NS
6 price IF Good Ideal 5 4 1.0 1.01 NS
7 price SI1 Fair Good 5 4 1.0 1.01 NS
8 price SI1 Fair Ideal 5 5 1.0 1.01 NS
9 price SI1 Good Ideal 4 5 0.41 1.01 NS
10 price SI2 Fair Good 4 4 0.057 1.01 NS
11 price SI2 Fair Ideal 4 4 0.057 1.01 NS
12 price SI2 Good Ideal 4 4 0.69 1.01 NS
13 price VS1 Fair Good 3 2 0.20 1.01 NS
14 price VS1 Fair Ideal 3 5 0.036 0.05 *
15 price VS1 Good Ideal 2 5 0.57 1.01 NS
16 price VS2 Fair Good 5 4 0.41 1.01 NS
17 price VS2 Fair Ideal 5 2 0.86 1.01 NS
18 price VS2 Good Ideal 4 2 0.80 1.01 NS
19 price VVS1 Fair Good 5 4 0.90 1.01 NS
20 price VVS1 Fair Ideal 5 5 0.15 1.01 NS
21 price VVS1 Good Ideal 4 5 0.19 1.01 NS
22 price VVS2 Fair Good 4 3 0.63 1.01 NS
23 price VVS2 Fair Ideal 4 5 0.032 0.05 *
24 price VVS2 Good Ideal 3 5 0.071 1.01 NS
stat_test
Code
stat_test(mini_diamond, y = price, x = cut) %>% print(width = Inf, n = Inf)
Output
# A tibble: 3 x 8
y group1 group2 n1 n2 p plim psymbol
<chr> <chr> <chr> <int> <int> <chr> <dbl> <chr>
1 price Fair Good 35 31 0.041 0.05 *
2 price Fair Ideal 35 34 0.018 0.05 *
3 price Good Ideal 31 34 0.93 1.01 NS
stat_test, exclude_func
Code
stat_test(df, x = coord, y = value, paired = TRUE, paired_by = id,
exclude_func = ~ abs(.x - .y) < 0.1)
Output
exclude 92 data pair because of exclude_func
# A tibble: 1 x 8
y group1 group2 n1 n2 p plim psymbol
<chr> <chr> <chr> <int> <int> <chr> <dbl> <chr>
1 value x y 100 100 0.0078 0.01 **
stat_test, one side NA
Code
stat_test(df, x = type, y = value, .by = cut, paired = TRUE, paired_by = id)
Output
# A tibble: 2 x 9
y cut group1 group2 n1 n2 p plim psymbol
<chr> <chr> <chr> <chr> <int> <int> <chr> <dbl> <chr>
1 value Good x y 31 31 0.65 1.01 NS
2 value Ideal x y 34 34 0.047 0.05 *
stat_fc
Code
stat_fc(mini_diamond, y = price, x = cut, .by = clarity) %>% print(n = Inf)
Output
# A tibble: 24 x 8
y clarity group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 price I1 Fair Good 4695. 2760. 1.70 1.7x
2 price I1 Fair Ideal 4695. 4249 1.11 1.1x
3 price I1 Good Ideal 2760. 4249 0.649 0.65x
4 price IF Fair Good 2016 1044. 1.93 1.9x
5 price IF Fair Ideal 2016 962. 2.10 2.1x
6 price IF Good Ideal 1044. 962. 1.09 1.1x
7 price SI1 Fair Good 5844. 3227. 1.81 1.8x
8 price SI1 Fair Ideal 5844. 3877. 1.51 1.5x
9 price SI1 Good Ideal 3227. 3877. 0.832 0.83x
10 price SI2 Fair Good 13162. 6539. 2.01 2.0x
11 price SI2 Fair Ideal 13162. 4267. 3.08 3.1x
12 price SI2 Good Ideal 6539. 4267. 1.53 1.5x
13 price VS1 Fair Good 6228. 775 8.04 8.0x
14 price VS1 Fair Ideal 6228. 2256. 2.76 2.8x
15 price VS1 Good Ideal 775 2256. 0.343 0.34x
16 price VS2 Fair Good 3529. 5582. 0.632 0.63x
17 price VS2 Fair Ideal 3529. 3024. 1.17 1.2x
18 price VS2 Good Ideal 5582. 3024. 1.85 1.8x
19 price VVS1 Fair Good 2184 2810. 0.777 0.78x
20 price VVS1 Fair Ideal 2184 4652. 0.469 0.47x
21 price VVS1 Good Ideal 2810. 4652. 0.604 0.60x
22 price VVS2 Fair Good 3543 7481. 0.474 0.47x
23 price VVS2 Fair Ideal 3543 1072. 3.31 3.3x
24 price VVS2 Good Ideal 7481. 1072. 6.98 7.0x
stat_fc, rev_div=TRUE
Code
stat_fc(mini_diamond, y = price, x = cut, rev_div = TRUE, .by = clarity) %>%
print(n = Inf)
Output
# A tibble: 24 x 8
y clarity group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 price I1 Fair Good 4695. 2760. 0.588 0.59x
2 price I1 Fair Ideal 4695. 4249 0.905 0.90x
3 price I1 Good Ideal 2760. 4249 1.54 1.5x
4 price IF Fair Good 2016 1044. 0.518 0.52x
5 price IF Fair Ideal 2016 962. 0.477 0.48x
6 price IF Good Ideal 1044. 962. 0.921 0.92x
7 price SI1 Fair Good 5844. 3227. 0.552 0.55x
8 price SI1 Fair Ideal 5844. 3877. 0.663 0.66x
9 price SI1 Good Ideal 3227. 3877. 1.20 1.2x
10 price SI2 Fair Good 13162. 6539. 0.497 0.50x
11 price SI2 Fair Ideal 13162. 4267. 0.324 0.32x
12 price SI2 Good Ideal 6539. 4267. 0.653 0.65x
13 price VS1 Fair Good 6228. 775 0.124 0.12x
14 price VS1 Fair Ideal 6228. 2256. 0.362 0.36x
15 price VS1 Good Ideal 775 2256. 2.91 2.9x
16 price VS2 Fair Good 3529. 5582. 1.58 1.6x
17 price VS2 Fair Ideal 3529. 3024. 0.857 0.86x
18 price VS2 Good Ideal 5582. 3024. 0.542 0.54x
19 price VVS1 Fair Good 2184 2810. 1.29 1.3x
20 price VVS1 Fair Ideal 2184 4652. 2.13 2.1x
21 price VVS1 Good Ideal 2810. 4652. 1.66 1.7x
22 price VVS2 Fair Good 3543 7481. 2.11 2.1x
23 price VVS2 Fair Ideal 3543 1072. 0.303 0.30x
24 price VVS2 Good Ideal 7481. 1072. 0.143 0.14x
stat_fc, method='median'
Code
suppressWarnings(stat_fc(mini_diamond, y = price, x = cut, .by = clarity,
method = "median") %>% print(n = Inf))
Output
# A tibble: 24 x 8
y clarity group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 price I1 Fair Good 5667 2143 2.64 2.6x
2 price I1 Fair Ideal 5667 3024 1.87 1.9x
3 price I1 Good Ideal 2143 3024 0.709 0.71x
4 price IF Fair Good 1826. 1052 1.74 1.7x
5 price IF Fair Ideal 1826. 877 2.08 2.1x
6 price IF Good Ideal 1052 877 1.20 1.2x
7 price SI1 Fair Good 3027 3533 0.857 0.86x
8 price SI1 Fair Ideal 3027 5370 0.564 0.56x
9 price SI1 Good Ideal 3533 5370 0.658 0.66x
10 price SI2 Fair Good 14716. 5671 2.59 2.6x
11 price SI2 Fair Ideal 14716. 3086. 4.77 4.8x
12 price SI2 Good Ideal 5671 3086. 1.84 1.8x
13 price VS1 Fair Good 6115 775 7.89 7.9x
14 price VS1 Fair Ideal 6115 2498 2.45 2.4x
15 price VS1 Good Ideal 775 2498 0.310 0.31x
16 price VS2 Fair Good 2815 3746. 0.751 0.75x
17 price VS2 Fair Ideal 2815 3024. 0.931 0.93x
18 price VS2 Good Ideal 3746. 3024. 1.24 1.2x
19 price VVS1 Fair Good 1691 1314 1.29 1.3x
20 price VVS1 Fair Ideal 1691 3487 0.485 0.48x
21 price VVS1 Good Ideal 1314 3487 0.377 0.38x
22 price VVS2 Fair Good 3800 6748 0.563 0.56x
23 price VVS2 Fair Ideal 3800 854 4.45 4.4x
24 price VVS2 Good Ideal 6748 854 7.90 7.9x
stat_fc, method='geom_mean'
Code
stat_fc(mini_diamond, y = price, x = cut, .by = clarity, method = "geom_mean") %>%
print(n = Inf)
Output
# A tibble: 24 x 8
y clarity group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 price I1 Fair Good 3911. 1571. 2.49 2.5x
2 price I1 Fair Ideal 3911. 3611. 1.08 1.1x
3 price I1 Good Ideal 1571. 3611. 0.435 0.44x
4 price IF Fair Good 1874. 961. 1.95 1.9x
5 price IF Fair Ideal 1874. 950. 1.97 2.0x
6 price IF Good Ideal 961. 950. 1.01 1.0x
7 price SI1 Fair Good 3833. 2401. 1.60 1.6x
8 price SI1 Fair Ideal 3833. 3268. 1.17 1.2x
9 price SI1 Good Ideal 2401. 3268. 0.735 0.73x
10 price SI2 Fair Good 12609. 4605. 2.74 2.7x
11 price SI2 Fair Ideal 12609. 3319. 3.80 3.8x
12 price SI2 Good Ideal 4605. 3319. 1.39 1.4x
13 price VS1 Fair Good 6194. 754. 8.21 8.2x
14 price VS1 Fair Ideal 6194. 1641. 3.77 3.8x
15 price VS1 Good Ideal 754. 1641. 0.459 0.46x
16 price VS2 Fair Good 3330. 4728. 0.704 0.70x
17 price VS2 Fair Ideal 3330. 1845. 1.80 1.8x
18 price VS2 Good Ideal 4728. 1845. 2.56 2.6x
19 price VVS1 Fair Good 1863. 1773. 1.05 1.1x
20 price VVS1 Fair Ideal 1863. 4052. 0.460 0.46x
21 price VVS1 Good Ideal 1773. 4052. 0.438 0.44x
22 price VVS2 Fair Good 3184. 4688. 0.679 0.68x
23 price VVS2 Fair Ideal 3184. 967. 3.29 3.3x
24 price VVS2 Good Ideal 4688. 967. 4.85 4.8x
stat_fc, one side NA
Code
stat_fc(df, x = type, y = value, .by = cut)
Output
# A tibble: 2 x 8
y cut group1 group2 y1 y2 fc fc_fmt
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr>
1 value Good x y 5.65 5.65 0.999 1.00x
2 value Ideal x y 5.57 5.59 0.997 1.00x
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