Не могу найти столбцы в R

Question

Я довольно новичок в R.

Я в процессе переоборудования кода с использования "10, Total All Industries" до "1013 Производство" в качестве фильтра в приведенном ниже коде.

В общем процессе я беру данные из двух .csv файлов, вычисляя среднее значение за год, а затем ранжирую на основе идентификатора.

Я получаю ошибку ниже.

   "Error: Can't find columns `JulyEmployment`, `AugustEmployment`, 
   `SeptemberEmployment` in `.data`."

Мой основной вопрос заключается в том, следует ли мне отрегулировать буквы c и l, которые продолжают слово / фразу, сохраняет?

В предыдущей версии переменные были текущими и последний без м.

 currentm %>%
 filter(AreaType=="State" & Ownership=="Private" & Industry=="1013 
 Manufacturing")->currentm
 lastm %>%
 filter(AreaType=="State" & Ownership=="Private" & Industry=="1013 
 Manufacturing")->lastm


 keepsc <- 
 c("St","Year","JulyEmployment","AugustEmployment","SeptemberEmployment")
 current<- current[keepsc]

 keepsl <- c("St","JulyEmployment","AugustEmployment","SeptemberEmployment")
 last<- last[keepsl]



  sample data

  structure(list(`Area
  Code` = c("1000", "2000", "4000", "5000", 
  "6000", "8000"), St = c("1", "2", "4", "5", "6", "8"), Cnty = c(0, 
  0, 0, 0, 0, 0), Own = c(5, 5, 5, 5, 5, 5), NAICS = c(1013, 1013, 
  1013, 1013, 1013, 1013), Year = c(2018, 2018, 2018, 2018, 2018, 
  2018), Qtr = c(3, 3, 3, 3, 3, 3), AreaType = c("State", "State", 
  "State", "State", "State", "State"), StName = c("Alabama", "Alaska", 
  "Arizona", "Arkansas", "California", "Colorado"), Area = c("Alabama -- 
  Statewide", 
  "Alaska -- Statewide", "Arizona -- Statewide", "Arkansas -- Statewide", 
  "California -- Statewide", "Colorado -- Statewide"), Ownership = 
  c("Private", 
  "Private", "Private", "Private", "Private", "Private"), Industry = c("1013 
  Manufacturing", 
  "1013 Manufacturing", "1013 Manufacturing", "1013 Manufacturing", 
  "1013 Manufacturing", "1013 Manufacturing"), StatusCode = c(NA_character_, 
  NA_character_, NA_character_, NA_character_, NA_character_, NA_character_
  ), EstablishmentCount = c(5582, 590, 5006, 2923, 43616, 5807), 
  JulyEmployment = c(267000, 23611, 170553, 160677, 1330268, 
  148444), AugustEmployment = c(267558, 19253, 170715, 160761, 
  1334919, 148235), SeptemberEmployment = c(267609, 13392, 
  170936, 161102, 1332249, 147649), TotalQuarterlyWages = c(3684759051, 
  252044635, 3013769930, 1905042213, 29819289717, 2502830607
  ), AverageWeeklyWage = c(1060, 1034, 1358, 911, 1721, 1300
  ), EmploymentLocationQuotientRelativetoU.S. = c(1.57, 0.46, 
  0.7, 1.52, 0.88, 0.64), TotalWageLocationQuotientRelativetoU.S. = c(1.58, 
  0.52, 0.83, 1.46, 1.02, 0.63)), class = c("tbl_df", "tbl", 
  "data.frame"), row.names = c(NA, -6L), .Names = c("Area\nCode", 
  "St", "Cnty", "Own", "NAICS", "Year", "Qtr", "AreaType", "StName", 
  "Area", "Ownership", "Industry", "StatusCode", "EstablishmentCount", 
  "JulyEmployment", "AugustEmployment", "SeptemberEmployment", 
  "TotalQuarterlyWages", "AverageWeeklyWage", 
  "EmploymentLocationQuotientRelativetoU.S.", 
  "TotalWageLocationQuotientRelativetoU.S."))