tests/testthat/test-row.R
In OuhscBbmc/OuhscMunge: Data Manipulation Operations
library(testthat)
test_that("mtcars -engine_sum", {
expected <- structure(
list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3,
24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4,
30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8,
19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8,
8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4),
disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8,
167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7,
71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145,
301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95,
123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150,
150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9,
3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,
3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76,
3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11
), wt = c(2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19,
3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2,
1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14,
1.513, 3.17, 2.77, 3.57, 2.78), qsec = c(16.46, 17.02, 18.61,
19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6,
18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87,
17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6
), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1), am = c(1,
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4, 4, 3,
3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3,
3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4,
2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1,
2, 2, 4, 6, 8, 2), engine_sum = c(170, 170, 114, 266, 370,
233, 372, 153.7, 147.8, 178.6, 178.6, 286.8, 286.8, 286.8,
484, 472, 452, 84.7, 82.7, 77.1, 126.1, 328, 314, 362, 410,
85, 126.3, 102.1, 363, 157, 317, 128)), row.names = c("Mazda RX4",
"Mazda RX4 Wag", "Datsun 710", "Hornet 4 Drive", "Hornet Sportabout",
"Valiant", "Duster 360", "Merc 240D", "Merc 230", "Merc 280",
"Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood",
"Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic",
"Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin",
"Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2",
"Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora",
"Volvo 142E"), class = "data.frame"
)
actual <-
mtcars |>
row_sum(
columns_to_average = c("cyl", "disp", "vs", "carb"),
new_column_name = "engine_sum"
)
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
test_that("mtcars -engine_sum & nonmissing count", {
expected <-
structure(
list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3,
24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4,
30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8,
19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8,
8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4),
disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8,
167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7,
71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145,
301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95,
123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150,
150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9,
3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,
3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76,
3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11
), wt = c(2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19,
3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2,
1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14,
1.513, 3.17, 2.77, 3.57, 2.78), qsec = c(16.46, 17.02, 18.61,
19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6,
18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87,
17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6
), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1), am = c(1,
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4, 4, 3,
3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3,
3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4,
2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1,
2, 2, 4, 6, 8, 2), engine_sum = c(170, 170, 114, 266, 370,
233, 372, 153.7, 147.8, 178.6, 178.6, 286.8, 286.8, 286.8,
484, 472, 452, 84.7, 82.7, 77.1, 126.1, 328, 314, 362, 410,
85, 126.3, 102.1, 363, 157, 317, 128), engine_nonmissing_count = c(4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)), row.names = c("Mazda RX4",
"Mazda RX4 Wag", "Datsun 710", "Hornet 4 Drive", "Hornet Sportabout",
"Valiant", "Duster 360", "Merc 240D", "Merc 230", "Merc 280",
"Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood",
"Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic",
"Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin",
"Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2",
"Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora",
"Volvo 142E"), class = "data.frame"
)
actual <-
mtcars |>
row_sum(
columns_to_average = c("cyl", "disp", "vs", "carb"),
new_column_name = "engine_sum",
nonmissing_count_name = "engine_nonmissing_count"
)
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
test_that("billboard -all weeks", {
expected <-
c(
NA, NA, 1403, 1342, 1012, 753, NA, 1041, 533, 1355, 839, 419,
531, 463, 1025, NA, 2328, NA, 1641, 751, 957, 647, 950, 561,
570, 903, 647, 1250, 713, 1086, 788, NA, 1283, 1070, 1300, 626,
1110, 768, 766, 871, 1032, 777, 1143, NA, NA, 916, 1460, NA,
675, 946, 904, NA, 740, 994, NA, 812, 1189, 1173, 1011, NA, 1249,
946, 2101, 1590, 1153, NA, 806, 877, 1492, 902, 1362, 968, 1371,
NA, 415, 734, 668, 1084, NA, 696, 753, 969, 759, 942, 865, 865,
1162, 753, 996, NA, 614, 301, 1021, 624, 698, NA, NA, 1094, NA,
974, 655, 1067, 1033, 683, 833, NA, NA, NA, 1383, 1226, 1039,
1038, 1000, 585, 1176, 549, NA, 1166, 1426, 1499, 773, 1220,
973, 692, NA, 1025, 1373, 616, 500, 685, 982, 668, 1181, 317,
1039, 1078, 623, 1162, 1149, 951, 698, 753, 466, 555, 626, 734,
1318, 494, 1140, 933, 1322, 1128, 913, 910, NA, 892, 1044, 909,
814, NA, 780, 724, 765, NA, NA, NA, NA, 1315, NA, 683, 915, 950,
780, 771, NA, 753, 949, 1669, 1342, 1470, 1206, 998, 1195, 1179,
NA, 1142, 855, 748, 1434, 1853, 387, 323, NA, 965, 668, 1118,
NA, 1263, 921, 1439, 1121, 994, 884, 910, 704, 882, 864, 1722,
844, NA, 1090, 829, 1476, 552, 1013, 589, 1215, 661, 328, 542,
510, 1172, 1050, 592, 715, NA, 811, 850, 712, NA, 1098, 1305,
NA, 588, 596, 605, NA, 1603, 945, NA, NA, 946, 1180, 1236, 1476,
796, 816, 1659, 890, 1278, 518, 1057, 273, 931, 573, NA, 1261,
614, NA, 1216, 718, NA, 1241, 632, 537, 1652, 748, NA, 1287,
531, 998, 1090, 530, 720, NA, 888, 988, 1128, 1255, 1214, 894,
1169, NA, NA, NA, 958, 569, 1324, 728, 938, 1339, 997, 991, NA,
1052, NA, 1152, NA, 1259, 1143, 879, 777, 643, 617, 992, 1270,
NA, 867, 1433, 1077, 1283, 773, 665, NA, 1244, NA, 727
)
actual <-
tidyr::billboard |>
row_sum(
pattern = "^wk\\d{1,2}$",
new_column_name = "week_sum",
threshold_proportion = .1,
verbose = TRUE
) |>
dplyr::pull(week_sum)
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
test_that("billboard -all weeks nonmissing count", {
expected <-
c(
7, 3, 53, 20, 18, 20, 5, 20, 32, 20, 11, 21, 22, 24, 20, 5,
29, 3, 20, 32, 20, 20, 31, 20, 24, 15, 20, 20, 21, 15, 9, 3,
15, 17, 20, 29, 15, 9, 23, 12, 20, 37, 20, 3, 3, 20, 19, 6, 8,
11, 10, 7, 20, 15, 7, 11, 20, 17, 12, 6, 19, 20, 57, 47, 13,
5, 17, 21, 20, 11, 18, 20, 20, 3, 28, 32, 32, 14, 6, 28, 10,
20, 15, 20, 20, 20, 13, 28, 14, 2, 20, 21, 15, 19, 10, 4, 1,
20, 5, 16, 21, 17, 12, 20, 21, 1, 7, 1, 20, 19, 15, 12, 20, 27,
20, 11, 7, 12, 20, 20, 8, 53, 14, 14, 4, 13, 19, 11, 28, 9, 20,
12, 18, 20, 17, 17, 20, 20, 17, 15, 20, 24, 24, 8, 20, 9, 15,
21, 19, 44, 17, 15, 20, 32, 6, 24, 15, 20, 12, 5, 20, 9, 10,
5, 4, 2, 3, 20, 5, 8, 20, 11, 9, 10, 7, 13, 11, 18, 17, 55, 20,
20, 17, 14, 7, 19, 22, 12, 18, 20, 9, 24, 5, 18, 18, 20, 1, 20,
13, 20, 20, 21, 20, 14, 8, 13, 20, 20, 10, 6, 20, 9, 23, 22,
20, 30, 17, 20, 23, 25, 26, 16, 34, 21, 27, 5, 13, 9, 9, 4, 20,
20, 6, 27, 32, 8, 4, 20, 20, 5, 5, 14, 20, 20, 19, 22, 20, 20,
25, 20, 26, 20, 26, 20, 33, 2, 20, 9, 5, 15, 16, 6, 20, 26, 28,
20, 26, 4, 26, 24, 24, 20, 11, 20, 3, 12, 26, 13, 17, 20, 20,
20, 7, 6, 5, 12, 22, 20, 20, 11, 20, 27, 11, 4, 22, 2, 16, 7,
19, 20, 41, 21, 12, 9, 11, 20, 6, 20, 19, 18, 15, 10, 8, 6, 14,
2, 39
)
actual <-
tidyr::billboard |>
row_sum(
pattern = "^wk\\d{1,2}$",
new_column_name = "week_sum",
threshold_proportion = .1,
nonmissing_count_name = "nonmissing_count",
verbose = FALSE
) |>
dplyr::pull(nonmissing_count)
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
test_that("billboard -subset", {
expected <-
c(
598, NA, 567, 601, 319, 202, NA, 422, 259, 606, 664, 248, 241,
207, 416, NA, 772, NA, 697, 335, 381, 302, 436, 156, 280, 390,
342, 644, 443, 571, 788, NA, 729, 472, 537, 313, 659, 668, 514,
585, 420, 271, 407, NA, NA, 504, 746, NA, 675, 772, 812, 434,
398, 511, 634, 630, 506, 608, 754, NA, 473, 468, 577, 668, 809,
NA, 331, 470, 720, 708, 583, 438, 745, NA, 274, 478, 325, 616,
NA, 411, 662, 508, 234, 503, 366, 428, 772, 497, 578, NA, 174,
112, 524, 171, 612, NA, NA, 501, NA, 489, 363, 540, 770, 443,
496, NA, 655, NA, 614, 602, 587, 787, 376, 287, 564, 380, 362,
881, 716, 608, 677, 423, 616, 362, NA, 648, 561, 461, 252, 685,
412, 452, 572, 219, 529, 601, 358, 509, 579, 487, 207, 413, 270,
555, 314, 734, 790, 247, 500, 461, 618, 565, 464, 576, NA, 447,
604, 462, 582, NA, 324, 724, 665, NA, NA, NA, NA, 511, NA, 683,
233, 768, 588, 674, 687, 448, 756, 845, 632, 379, 566, 509, 552,
789, 608, 505, 474, 460, 715, 839, 387, 102, NA, 441, 180, 467,
NA, 521, 621, 625, 591, 543, 423, 572, 704, 595, 451, 736, 749,
NA, 465, 829, 406, 374, 537, 360, 554, 404, 131, 318, 170, 588,
541, 371, 403, NA, 440, 850, 712, NA, 437, 602, NA, 331, 114,
605, NA, 749, 215, NA, NA, 594, 607, 636, 693, 478, 431, 749,
556, 510, 206, 424, 44, 358, 243, NA, 534, 614, NA, 699, 299,
NA, 540, 385, 296, 638, 343, NA, 653, 254, 515, 341, 344, 208,
NA, 604, 528, 752, 611, 494, 448, 384, 443, NA, NA, 673, 253,
514, 352, 749, 498, 447, 802, NA, 600, NA, 610, 486, 517, 521,
382, 358, 457, 617, 802, 478, NA, 525, 592, 429, 785, 675, 665,
NA, 764, NA, 240
)
expected_message <- "The following columns will be summed:\n- wk1\n- wk2\n- wk3\n- wk4\n- wk5\n- wk6\n- wk7\n- wk8\n- wk9"
expect_message(
regexp = expected_message,{
actual <-
tidyr::billboard |>
row_sum(
pattern = "^wk\\d$",
new_column_name = "week_sum",
nonmissing_count_name = "nonmissing_count",
verbose = TRUE
) |>
dplyr::pull(week_sum)
})
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
OuhscBbmc/OuhscMunge documentation built on March 2, 2024, 11:44 a.m.
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library(testthat)
test_that("mtcars -engine_sum", {
expected <- structure(
list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3,
24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4,
30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8,
19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8,
8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4),
disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8,
167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7,
71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145,
301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95,
123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150,
150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9,
3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,
3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76,
3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11
), wt = c(2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19,
3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2,
1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14,
1.513, 3.17, 2.77, 3.57, 2.78), qsec = c(16.46, 17.02, 18.61,
19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6,
18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87,
17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6
), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1), am = c(1,
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4, 4, 3,
3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3,
3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4,
2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1,
2, 2, 4, 6, 8, 2), engine_sum = c(170, 170, 114, 266, 370,
233, 372, 153.7, 147.8, 178.6, 178.6, 286.8, 286.8, 286.8,
484, 472, 452, 84.7, 82.7, 77.1, 126.1, 328, 314, 362, 410,
85, 126.3, 102.1, 363, 157, 317, 128)), row.names = c("Mazda RX4",
"Mazda RX4 Wag", "Datsun 710", "Hornet 4 Drive", "Hornet Sportabout",
"Valiant", "Duster 360", "Merc 240D", "Merc 230", "Merc 280",
"Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood",
"Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic",
"Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin",
"Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2",
"Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora",
"Volvo 142E"), class = "data.frame"
)
actual <-
mtcars |>
row_sum(
columns_to_average = c("cyl", "disp", "vs", "carb"),
new_column_name = "engine_sum"
)
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
test_that("mtcars -engine_sum & nonmissing count", {
expected <-
structure(
list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3,
24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4,
30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8,
19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8,
8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4),
disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8,
167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7,
71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145,
301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95,
123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150,
150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9,
3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,
3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76,
3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11
), wt = c(2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19,
3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2,
1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14,
1.513, 3.17, 2.77, 3.57, 2.78), qsec = c(16.46, 17.02, 18.61,
19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6,
18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87,
17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6
), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1), am = c(1,
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4, 4, 3,
3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3,
3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4,
2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1,
2, 2, 4, 6, 8, 2), engine_sum = c(170, 170, 114, 266, 370,
233, 372, 153.7, 147.8, 178.6, 178.6, 286.8, 286.8, 286.8,
484, 472, 452, 84.7, 82.7, 77.1, 126.1, 328, 314, 362, 410,
85, 126.3, 102.1, 363, 157, 317, 128), engine_nonmissing_count = c(4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)), row.names = c("Mazda RX4",
"Mazda RX4 Wag", "Datsun 710", "Hornet 4 Drive", "Hornet Sportabout",
"Valiant", "Duster 360", "Merc 240D", "Merc 230", "Merc 280",
"Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood",
"Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic",
"Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin",
"Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2",
"Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora",
"Volvo 142E"), class = "data.frame"
)
actual <-
mtcars |>
row_sum(
columns_to_average = c("cyl", "disp", "vs", "carb"),
new_column_name = "engine_sum",
nonmissing_count_name = "engine_nonmissing_count"
)
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
test_that("billboard -all weeks", {
expected <-
c(
NA, NA, 1403, 1342, 1012, 753, NA, 1041, 533, 1355, 839, 419,
531, 463, 1025, NA, 2328, NA, 1641, 751, 957, 647, 950, 561,
570, 903, 647, 1250, 713, 1086, 788, NA, 1283, 1070, 1300, 626,
1110, 768, 766, 871, 1032, 777, 1143, NA, NA, 916, 1460, NA,
675, 946, 904, NA, 740, 994, NA, 812, 1189, 1173, 1011, NA, 1249,
946, 2101, 1590, 1153, NA, 806, 877, 1492, 902, 1362, 968, 1371,
NA, 415, 734, 668, 1084, NA, 696, 753, 969, 759, 942, 865, 865,
1162, 753, 996, NA, 614, 301, 1021, 624, 698, NA, NA, 1094, NA,
974, 655, 1067, 1033, 683, 833, NA, NA, NA, 1383, 1226, 1039,
1038, 1000, 585, 1176, 549, NA, 1166, 1426, 1499, 773, 1220,
973, 692, NA, 1025, 1373, 616, 500, 685, 982, 668, 1181, 317,
1039, 1078, 623, 1162, 1149, 951, 698, 753, 466, 555, 626, 734,
1318, 494, 1140, 933, 1322, 1128, 913, 910, NA, 892, 1044, 909,
814, NA, 780, 724, 765, NA, NA, NA, NA, 1315, NA, 683, 915, 950,
780, 771, NA, 753, 949, 1669, 1342, 1470, 1206, 998, 1195, 1179,
NA, 1142, 855, 748, 1434, 1853, 387, 323, NA, 965, 668, 1118,
NA, 1263, 921, 1439, 1121, 994, 884, 910, 704, 882, 864, 1722,
844, NA, 1090, 829, 1476, 552, 1013, 589, 1215, 661, 328, 542,
510, 1172, 1050, 592, 715, NA, 811, 850, 712, NA, 1098, 1305,
NA, 588, 596, 605, NA, 1603, 945, NA, NA, 946, 1180, 1236, 1476,
796, 816, 1659, 890, 1278, 518, 1057, 273, 931, 573, NA, 1261,
614, NA, 1216, 718, NA, 1241, 632, 537, 1652, 748, NA, 1287,
531, 998, 1090, 530, 720, NA, 888, 988, 1128, 1255, 1214, 894,
1169, NA, NA, NA, 958, 569, 1324, 728, 938, 1339, 997, 991, NA,
1052, NA, 1152, NA, 1259, 1143, 879, 777, 643, 617, 992, 1270,
NA, 867, 1433, 1077, 1283, 773, 665, NA, 1244, NA, 727
)
actual <-
tidyr::billboard |>
row_sum(
pattern = "^wk\\d{1,2}$",
new_column_name = "week_sum",
threshold_proportion = .1,
verbose = TRUE
) |>
dplyr::pull(week_sum)
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
test_that("billboard -all weeks nonmissing count", {
expected <-
c(
7, 3, 53, 20, 18, 20, 5, 20, 32, 20, 11, 21, 22, 24, 20, 5,
29, 3, 20, 32, 20, 20, 31, 20, 24, 15, 20, 20, 21, 15, 9, 3,
15, 17, 20, 29, 15, 9, 23, 12, 20, 37, 20, 3, 3, 20, 19, 6, 8,
11, 10, 7, 20, 15, 7, 11, 20, 17, 12, 6, 19, 20, 57, 47, 13,
5, 17, 21, 20, 11, 18, 20, 20, 3, 28, 32, 32, 14, 6, 28, 10,
20, 15, 20, 20, 20, 13, 28, 14, 2, 20, 21, 15, 19, 10, 4, 1,
20, 5, 16, 21, 17, 12, 20, 21, 1, 7, 1, 20, 19, 15, 12, 20, 27,
20, 11, 7, 12, 20, 20, 8, 53, 14, 14, 4, 13, 19, 11, 28, 9, 20,
12, 18, 20, 17, 17, 20, 20, 17, 15, 20, 24, 24, 8, 20, 9, 15,
21, 19, 44, 17, 15, 20, 32, 6, 24, 15, 20, 12, 5, 20, 9, 10,
5, 4, 2, 3, 20, 5, 8, 20, 11, 9, 10, 7, 13, 11, 18, 17, 55, 20,
20, 17, 14, 7, 19, 22, 12, 18, 20, 9, 24, 5, 18, 18, 20, 1, 20,
13, 20, 20, 21, 20, 14, 8, 13, 20, 20, 10, 6, 20, 9, 23, 22,
20, 30, 17, 20, 23, 25, 26, 16, 34, 21, 27, 5, 13, 9, 9, 4, 20,
20, 6, 27, 32, 8, 4, 20, 20, 5, 5, 14, 20, 20, 19, 22, 20, 20,
25, 20, 26, 20, 26, 20, 33, 2, 20, 9, 5, 15, 16, 6, 20, 26, 28,
20, 26, 4, 26, 24, 24, 20, 11, 20, 3, 12, 26, 13, 17, 20, 20,
20, 7, 6, 5, 12, 22, 20, 20, 11, 20, 27, 11, 4, 22, 2, 16, 7,
19, 20, 41, 21, 12, 9, 11, 20, 6, 20, 19, 18, 15, 10, 8, 6, 14,
2, 39
)
actual <-
tidyr::billboard |>
row_sum(
pattern = "^wk\\d{1,2}$",
new_column_name = "week_sum",
threshold_proportion = .1,
nonmissing_count_name = "nonmissing_count",
verbose = FALSE
) |>
dplyr::pull(nonmissing_count)
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
test_that("billboard -subset", {
expected <-
c(
598, NA, 567, 601, 319, 202, NA, 422, 259, 606, 664, 248, 241,
207, 416, NA, 772, NA, 697, 335, 381, 302, 436, 156, 280, 390,
342, 644, 443, 571, 788, NA, 729, 472, 537, 313, 659, 668, 514,
585, 420, 271, 407, NA, NA, 504, 746, NA, 675, 772, 812, 434,
398, 511, 634, 630, 506, 608, 754, NA, 473, 468, 577, 668, 809,
NA, 331, 470, 720, 708, 583, 438, 745, NA, 274, 478, 325, 616,
NA, 411, 662, 508, 234, 503, 366, 428, 772, 497, 578, NA, 174,
112, 524, 171, 612, NA, NA, 501, NA, 489, 363, 540, 770, 443,
496, NA, 655, NA, 614, 602, 587, 787, 376, 287, 564, 380, 362,
881, 716, 608, 677, 423, 616, 362, NA, 648, 561, 461, 252, 685,
412, 452, 572, 219, 529, 601, 358, 509, 579, 487, 207, 413, 270,
555, 314, 734, 790, 247, 500, 461, 618, 565, 464, 576, NA, 447,
604, 462, 582, NA, 324, 724, 665, NA, NA, NA, NA, 511, NA, 683,
233, 768, 588, 674, 687, 448, 756, 845, 632, 379, 566, 509, 552,
789, 608, 505, 474, 460, 715, 839, 387, 102, NA, 441, 180, 467,
NA, 521, 621, 625, 591, 543, 423, 572, 704, 595, 451, 736, 749,
NA, 465, 829, 406, 374, 537, 360, 554, 404, 131, 318, 170, 588,
541, 371, 403, NA, 440, 850, 712, NA, 437, 602, NA, 331, 114,
605, NA, 749, 215, NA, NA, 594, 607, 636, 693, 478, 431, 749,
556, 510, 206, 424, 44, 358, 243, NA, 534, 614, NA, 699, 299,
NA, 540, 385, 296, 638, 343, NA, 653, 254, 515, 341, 344, 208,
NA, 604, 528, 752, 611, 494, 448, 384, 443, NA, NA, 673, 253,
514, 352, 749, 498, 447, 802, NA, 600, NA, 610, 486, 517, 521,
382, 358, 457, 617, 802, 478, NA, 525, 592, 429, 785, 675, 665,
NA, 764, NA, 240
)
expected_message <- "The following columns will be summed:\n- wk1\n- wk2\n- wk3\n- wk4\n- wk5\n- wk6\n- wk7\n- wk8\n- wk9"
expect_message(
regexp = expected_message,{
actual <-
tidyr::billboard |>
row_sum(
pattern = "^wk\\d$",
new_column_name = "week_sum",
nonmissing_count_name = "nonmissing_count",
verbose = TRUE
) |>
dplyr::pull(week_sum)
})
# expected <- dput(actual)
testthat::expect_equal(actual, expected)
})
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