这些是我的数据集的前50行:
structure(list(price_used = c("comtrade_price_mult", NA, NA,
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"government", "government", "government", "government", "government",
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NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), yearvalue = c(76133438.9648438,
NA, NA, 62305808.59375, 62305808.59375, 1091597766.5625,
417448917.578125, 66877492.1875, 1171693663.125, 448079197.65625,
66877492.1875, 76446015.625, 512188304.6875, 1339334193.75,
76446015.625, 1643753775, 628604468.75, 418313269.921875,
1093857983.4375, 529067698.4375, 1383472548.75, 717797224.21875,
1876986174.375, 748939871.09375, NA, NA, 1958421871.875,
877859388, 847055412, 365471220, NA, 657848196, 426205320,
NA, 255723192, NA, 168767865, 303782157, 536430384, NA, 298016880,
912430656, 506905920, NA, 593088720, NA, 1067559696, 1312398288,
729110160, NA), price_mult = c(14501.607421875, NA, NA, 62305.80859375,
62305.80859375, 62305.80859375, 62305.80859375, 66877.4921875,
66877.4921875, 66877.4921875, 66877.4921875, 76446.015625,
76446.015625, 76446.015625, 76446.015625, 93821.5625, 93821.5625,
62434.81640625, 62434.81640625, 78965.328125, 78965.328125,
107133.9140625, 107133.9140625, 111782.0703125, 111782.0703125,
111782.0703125, 111782.0703125, 20901414, 20167986, 24364748,
NA, 24364748, 21310266, NA, 21310266, NA, 11251191, 11251191,
19867792, NA, 19867792, 33793728, 33793728, NA, 39539248,
NA, 39539248, 48607344, 48607344, NA), oil_gas = c(1, 0,
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1), gold = c(0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0), artisanal = c(0, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0)), row.names = c(NA, 50L), class = "data.frame")
我想知道对于NAME_0, year, standardmeasure, resource的每个唯一组合，变量comtrade_price_mult, wb_price_mult, usgs_price_mult和multicolour_price_mult有多少个不同的值。
结果应该看起来像:
year NAME_0 standardmeasure resource n_comtrade n_wb n_usgs n_multicolour
2004 Ghana kilogram gold 3 1 1 NA
2005 Namibia metric tons diamonds 2 1 NA 1
带NA表示只有NA值。
可能通过使用管道将n_distinct()和group_by()组合在一起?
使用group_by,summarise，…你可以这样做:
注意:如果只有NA值，我使用if来返回NA。还请注意，如果不想计算NAs，则必须将na.rm = TRUE添加到n_distinct。
library(dplyr)
df |>
group_by(year, NAME_0, standardmeasure, resource) |>
summarise(across(c(comtrade_price_mult, wb_price_mult, usgs_price_mult, multicolour_price_mult), ~ if (all(is.na(.x))) NA_integer_ else n_distinct(.x)), .groups = "drop") |>
rename_with(~ gsub("^(.*?)_price_mult$", "n_\1", .x), .cols = ends_with("price_mult"))
#> # A tibble: 27 × 8
#> year NAME_0 standardmeasure resource n_comtrade n_wb n_usgs n_multicolour
#> <dbl> <chr> <chr> <chr> <int> <int> <int> <int>
#> 1 1994 Egypt million 42-gallo… oil 1 1 NA NA
#> 2 1995 Egypt million 42-gallo… oil 1 1 NA NA
#> 3 1996 Egypt million 42-gallo… oil 1 1 NA NA
#> 4 1996 Egypt million cubic me… natural… NA NA NA NA
#> 5 1997 Egypt million 42-gallo… oil 1 1 NA NA
#> 6 1997 Egypt million cubic me… natural… NA NA NA NA
#> 7 1998 Egypt million 42-gallo… oil 1 1 NA NA
#> 8 1998 Egypt million cubic me… natural… NA NA NA NA
#> 9 1999 Egypt million 42-gallo… oil 1 1 NA NA
#> 10 1999 Egypt million cubic me… natural… NA NA NA NA
#> # … with 17 more rows