R 使用if-else的几个条件错误：找不到对象

我正在尝试使用if条件在R中创建一个新列

我想创建一个只包含M和F（男性和女性）以及“na”的列，而其他内容是，例如，M？还是空白

我的专栏

str（意大利2018年1月气候$sex）chr[1:3130]“F”“F”“M”“M”“F”“F” “F”“F”“F”“F”“F”“F”“F”“F”“M”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“F”“M”“F”“F”“F”“

而我正在创造的

Italy_Jan2018_Climate ["sex_adult"] <- NA

Italy_Jan2018_Climate$sex_adult <- 
  if(Italy_Jan2018_Climate$sex  ==F | Italy_Jan2018_Climate$sex  ==M){
  sex_adult == Italy_Jan2018_Climate$sex 
}else {
  sex_adult = na
}

提前感谢,，

---

mara

我看到多个语法错误。您应该能够使用以下一行程序执行此更新：

Italy_Jan2018_Climate$sex_adult <-
    ifelse(Italy_Jan2018_Climate$sex %in% c('M', 'F'),
           Italy_Jan2018_Climate$sex,
           NA)

意大利\u 2018年1月\u气候$sex\u成人
structure(list(abbpop = c("AL", "AL", "AL", "AL", "AL", "AL"), 
    label = c("AL03", "AL09", "AL10", "AL13", "AL15", "AL16"), 
    code = c("AL03", "AL09", "AL10", "AL13", "AL15", "AL16"), 
    number = c(330, 336, 337, 340, 342, 343), Year = c(2014, 
    2014, 2014, 2014, 2014, 2014), date = c(41739, 41739, 41739, 
    41739, 41739, 41739), country = c("ITA", "ITA", "ITA", "ITA", 
    "ITA", "ITA"), lineage = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), pop = c("Cerreto Alpi", "Cerreto Alpi", "Cerreto Alpi", 
    "Cerreto Alpi", "Cerreto Alpi", "Cerreto Alpi"), sex = c("F", 
    "F", "M", "M", "F", "F"), svl = c(60, 60, 59, 62, 60, 70), 
    tot = c(182, 160, 182, 193, 142, 145), mass = c(6.18, 4.6, 
    5.57, 5.97, 6, 8.41), headlength = c(12.6, 12.4, 14.7, 15.1, 
    12, 14.2), headwidth = c(6.6, 6, 7.7, 7.2, 6.1, 7.5), Tdorsal = c(1, 
    1, 1, 1, 1, 1), Gdorsal = c(1, 1, 1, 1, 1, 1), reg = c("0", 
    "0", "0", "0", "1", "1"), reglength = c(NA, NA, NA, NA, "45", 
    "67"), cops = c("4", "1", NA, NA, "3", "0"), scars = c("0", 
    "0", "0", "2", "0", "0"), notes = c("ovulated", "ovulated", 
    NA, NA, "ovulated", "ovulated, almost egy, slight tendency for red ventral, lost 02/300"
    ), green = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_), green2 = c(NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_), greenobj = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), blackness = c(0.03, 0.18, 0.42, 0.28, 0.07, 0.33), Bssize = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_, 
    NA_character_), biteforce = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), testes = c(NA_character_, NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_), Chest = c("W", 
    "W", "W", "W", "W", "W"), Throat = c("W", "W", "W", "W", 
    "W", "W"), `Mara green1` = c(NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_), `Mara green2` = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_, 
    NA_character_), Habitat = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), phenotype = c(1, 1, 1, 1, 1, 1), group_phenotype = c(1, 
    1, 1, 1, 1, 1), Latitude = c(44.322488, 44.322488, 44.322488, 
    44.322488, 44.322488, 44.322488), Longitude = c(10.25085, 
    10.25085, 10.25085, 10.25085, 10.25085, 10.25085), amt = c(16.9500001271566, 
    16.9500001271566, 16.9500001271566, 16.9500001271566, 16.9500001271566, 
    16.9500001271566), mdt = c(1.75000003973643, 1.75000003973643, 
    1.75000003973643, 1.75000003973643, 1.75000003973643, 1.75000003973643
    ), iso = c(1751, 1751, 1751, 1751, 1751, 1751), ts = c(233, 
    233, 233, 233, 233, 233), maxtwarm = c(58, 58, 58, 58, 58, 
    58), mintcoldm = c(33.4769734501678, 33.4769734501678, 33.4769734501678, 
    33.4769734501678, 33.4769734501678, 33.4769734501678), tar = c(627, 
    627, 627, 627, 627, 627), mintwetq = c(263, 263, 263, 263, 
    263, 263), mtdrq = c(263, 263, 263, 263, 263, 263), mtwarmq = c(263, 
    263, 263, 263, 263, 263), mtcoldq = c(475, 475, 475, 475, 
    475, 475), ap = c(8.47499991953373, 8.47499991953373, 8.47499991953373, 
    8.47499991953373, 8.47499991953373, 8.47499991953373), pwetm = c(33.6309526343735, 
    33.6309526343735, 33.6309526343735, 33.6309526343735, 33.6309526343735, 
    33.6309526343735), pdrm = c(622.587926122833, 622.587926122833, 
    622.587926122833, 622.587926122833, 622.587926122833, 622.587926122833
    ), ps = c(21.8999996185303, 21.8999996185303, 21.8999996185303, 
    21.8999996185303, 21.8999996185303, 21.8999996185303), pwetq = c(-3.29999995231628, 
    -3.29999995231628, -3.29999995231628, -3.29999995231628, 
    -3.29999995231628, -3.29999995231628), pdrq = c(25.1999995708466, 
    25.1999995708466, 25.1999995708466, 25.1999995708466, 25.1999995708466, 
    25.1999995708466), pwarmq = c(5.54999985297521, 5.54999985297521, 
    5.54999985297521, 5.54999985297521, 5.54999985297521, 5.54999985297521
    ), pcoldq = c(16.9500001271566, 16.9500001271566, 16.9500001271566, 
    16.9500001271566, 16.9500001271566, 16.9500001271566), sex_adult = c(NA, 
    NA, NA, NA, NA, NA)), .Names = c("abbpop", "label", "code", 
"number", "Year", "date", "country", "lineage", "pop", "sex", 
"svl", "tot", "mass", "headlength", "headwidth", "Tdorsal", "Gdorsal", 
"reg", "reglength", "cops", "scars", "notes", "green", "green2", 
"greenobj", "blackness", "Bssize", "biteforce", "testes", "Chest", 
"Throat", "Mara green1", "Mara green2", "Habitat", "phenotype", 
"group_phenotype", "Latitude", "Longitude", "amt", "mdt", "iso", 
"ts", "maxtwarm", "mintcoldm", "tar", "mintwetq", "mtdrq", "mtwarmq", 
"mtcoldq", "ap", "pwetm", "pdrm", "ps", "pwetq", "pdrq", "pwarmq", 
"pcoldq", "sex_adult"), row.names = c(NA, -6L), class = c("tbl_df", 
"tbl", "data.frame"))

Italy_Jan2018_Climate$sex_adult <-
    ifelse(Italy_Jan2018_Climate$sex %in% c('M', 'F'),
           Italy_Jan2018_Climate$sex,
           NA)