R 中带有和/或运算符的 IF/else 语句

Question

I have an idea of what I want to happen but I'm having trouble coming up with the correct If/then statement for it. There are three specific columns to focus on here: Niu, PVC, and Metal.

If there is a value for Niu but not PVC AND Metal, the row needs to be deleted. It's okay if there is a value for Niu that only has PVC or Metal. If Niu, PVC, and Metal are all Na that row needs to be kept in the data set.

So, the I want rows that have a value for Niu, but not PVC and Metal to be deleted.

Here is my data:

structure(list(Seq = c(1L, 2L, 3L, 5L, 6L, 7L), Pag = c(NA_character_, 
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_
), Nucli = structure(c(16L, NA, NA, 16L, NA, NA), .Label = c("2014", 
"2025", "2058", "2073", "2095/1003", "2106", "2140", "2162.7", 
"2195", "2195/3400", "2207.1/3254", "2207.4", "2318", "2329", 
"2407", "2419", "242.1", "2460", "2581", "2581.1", "2581.3", 
"2602", "2624", "2915", "3111", "3122", "3254", "3265", "3298", 
"3298.1", "3298.2", "3400", "3577", "401", "423", "424", "424.2", 
"613", "657", "691", "691.1", "691.2", "768", "78", "813", "813.2", 
"825", "825.2", "836", "836.1", "836.2", "863.1", "869", "869.1", 
"869.2", "981", "981.1", "981.3", "992", "BCN", "Desconegut", 
"P_BCN"), class = "factor"), Niu = structure(c(290L, NA, NA, 
298L, NA, NA), .Label = c("1", "10", "100", "101", "102", "102 verd", 
"103", "104", "105", "106", "107", "108", "109", "11", "110", 
"111", "1118", "112", "113", "114", "115", "116", "117", "118", 
"119", "12", "120", "121", "122", "122 verd", "123", "124", "125", 
"126", "127", "127 verde", "128", "129", "129 verd", "13", "130", 
"131", "132", "132 verd", "133", "134", "135", "136", "137", 
"138", "139", "14", "140", "141", "142", "143", "144", "145", 
"146", "147", "147 verde", "148", "149", "15", "150", "151", 
"152", "153", "154", "155", "156", "157", "158", "159", "159 verd", 
"16", "160", "161", "162", "163", "164", "165", "166", "167", 
"168", "169", "17", "170", "171", "172", "173", "174", "175", 
"176", "177", "178", "179", "18", "180", "181", "182", "183", 
"184", "185", "186", "187", "188", "189", "19", "190", "191", 
"192", "193", "194", "195", "2", "20", "200", "201", "202", "203", 
"204", "205", "205 verd", "206", "207", "208", "208 verd", "209", 
"21", "210", "212", "213", "214", "215", "216", "217", "218", 
"219", "22", "220", "221", "222", "223", "224", "225", "226", 
"227", "228", "229", "23", "230", "230 verde", "231", "232", 
"233", "234", "238", "239", "24", "244", "246", "248", "249", 
"25", "251", "252", "254", "255", "256", "258", "26", "261", 
"263", "264", "266", "267", "27", "271", "273", "276", "279", 
"28", "280", "287", "29", "29 verd", "291", "293", "294", "296", 
"299", "3", "30", "300 gris", "301 gris", "302 gris", "303 gris", 
"304 gris", "305 gris", "306 gris", "307 gris", "308 gris", "309", 
"31", "310 gris", "311 gris", "312", "314", "315 gris", "316 gris", 
"317 gris", "318", "32", "320 gris", "321", "322", "323", "324 gris", 
"325", "327 gris", "33", "331", "34", "343", "345", "35", "350", 
"354", "355", "357", "358", "36", "368", "37", "372", "38", "39", 
"4", "40", "41", "41 verde", "42", "429", "43", "430", "431", 
"433", "435", "436", "438", "439", "44", "440", "442", "444", 
"445", "45", "450", "455", "457", "46", "460", "464", "466", 
"47", "471", "475", "477", "48", "487", "489", "49", "5", "50", 
"500", "51", "52", "53", "54", "55", "56", "57", "58", "59", 
"6", "60", "61", "62", "63", "64", "65", "66", "67", "68", "69", 
"7", "7 vermell", "70", "71", "72", "72 verde", "73", "74", "75", 
"75 verd", "76", "77", "78", "781", "79", "8", "80", "81", "82", 
"83", "84", "85", "86", "87", "88", "89", "9", "90", "91", "92", 
"927", "93", "94", "941", "95", "96", "97", "98", "99", "A66", 
"NO_1", "NO_2", "NO_3", "NO_4", "V100", "V102", "V107", "V112", 
"V124", "V126", "V128", "V131", "V132", "V136", "V138", "V139", 
"V62", "V67", "V70", "V79", "V80", "V82", "V87", "V89", "V93", 
"V94", "V95", "V96"), class = "factor"), PVC = c("AMN1", NA, 
NA, "AV52", NA, NA), Metal = c(NA, NA, NA, "6168133", NA, NA), 
    Any.anellament.com.poll = c("2003", NA, NA, "2006", NA, NA
    ), DATA.D.ECLOSIO = c(NA_character_, NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_), DATA.DE.POSTA = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_, 
    NA_character_), ordre_ou = structure(c(8L, 8L, 8L, 8L, 8L, 
    8L), .Label = c("0", "1", "10", "2", "3", "4", "5", "9", 
    "a", "A", "b", "B", "c", "C"), class = "factor"), length = c(6236, 
    6396, 6116, 6162, 5992, 6307), width = c(4463, 4364, 4296, 
    4103, 4337, 4147), Year = structure(c(1L, 1L, 1L, 1L, 1L, 
    1L), .Label = c("2012", "2013", "2014", "2015", "2016", "2017", 
    "2018"), class = "factor")), row.names = c(NA, 6L), class = "data.frame")

Thanks in advance. Let me know if you have any questions

Answer 1

If I understand your requirements correctly, this should do it:

library(dplyr)

df %>% 
  mutate(keep = case_when(!is.na(Niu) & (!is.na(PVC) | !is.na(Metal)) ~ "yes",
                          !is.na(Niu) & (is.na(PVC) & is.na(Metal)) ~ "no",
                          is.na(Niu) & is.na(PVC) & is.na(Metal) ~ "yes")) %>% 
  filter(keep == "yes") %>% 
  select(-keep)