州名到縮寫使用R

Question

我有一個名稱爲MASTER的Excel文件，我有一個列名稱狀態。

州名是縮寫和全名的混合。我想要將所有全名轉換爲縮寫。我試過這個代碼，但我不知道我做錯了：

MASTER<- read.csv("c:\\users\\Desktop\\test merge\\MASTER.csv", header=T, sep=",") 
> MASTER = c("CALIFORNIA","ARIZONA","ARKANSAS","colorado","CONNECTICUT","DISTRICT OF COLUMBIA","FLORIDA","Georgia","hawaii","Illinois","Indiana","Iowa","kansas","Kentucky","LOUISIANA","Maine","Marryland","Massachusetts","Michigan","Minnesota","Missouri","MONTANA","NEBRASKA","Nevada","New Hampshire","New Jersey","NEW MEXICO","New York","North Carolina","OHIO","OKLAHOMA","Oregon","palmer","PANAMA","Pennsylvania","SOUTH CAROLINA","SOUTH DAKOTA","Tejas","Tennessee","Texas","TX.","UTAH","Virgin Islands","VIRGINIA","Washington","West Virginia","WISCONSIN","Wyoming") 
> MASTER$state <- state.abb[match(MASTER$state,state.name)] 
Error in `$<-.data.frame`(`*tmp*`, state, value = character(0)) : 
    replacement has 0 rows, data has 635768 

Answer 1

這可以幫助您開始，希望說明在這個過程中的幾個概念：

master <- c(
    "CALIFORNIA", "ARIZONA", "ARKANSAS", "colorado", "CONNECTICUT", "DISTRICT OF COLUMBIA", 
    "FLORIDA", "Georgia", "hawaii", "Illinois", "Indiana", "Iowa", "kansas", "Kentucky", 
    "LOUISIANA", "Maine", "Marryland", "Massachusetts", "Michigan", "Minnesota", "Missouri", 
    "MONTANA", "NEBRASKA", "Nevada", "New Hampshire", "New Jersey", "NEW MEXICO", "New York", 
    "North Carolina", "OHIO", "OKLAHOMA", "Oregon", "palmer", "PANAMA", "Pennsylvania", 
    "SOUTH CAROLINA", "SOUTH DAKOTA", "Tejas", "Tennessee", "Texas", "TX.", "UTAH", 
    "Virgin Islands", "VIRGINIA", "Washington", "West Virginia", "WISCONSIN", "Wyoming" 
) 

(master_low <- tolower(master)) 
## [1] "california"   "arizona"    "arkansas"    
## [4] "colorado"    "connecticut"   "district of columbia" 
## [7] "florida"    "georgia"    "hawaii"    
## [10] "illinois"    "indiana"    "iowa"     
## [13] "kansas"    "kentucky"    "louisiana"   
## [16] "maine"    "marryland"   "massachusetts"  
## [19] "michigan"    "minnesota"   "missouri"    
## [22] "montana"    "nebraska"    "nevada"    
## [25] "new hampshire"  "new jersey"   "new mexico"   
## [28] "new york"    "north carolina"  "ohio"     
## [31] "oklahoma"    "oregon"    "palmer"    
## [34] "panama"    "pennsylvania"   "south carolina"  
## [37] "south dakota"   "tejas"    "tennessee"   
## [40] "texas"    "tx."     "utah"     
## [43] "virgin islands"  "virginia"    "washington"   
## [46] "west virginia"  "wisconsin"   "wyoming" 

state_tbl <- setNames(state.abb, tolower(state.name)) 

data.frame(
    orig = master, 
    lower = master_low, 
    abbrev = state_tbl[master_low], 
    stringsAsFactors = FALSE 
) 
##     orig    lower abbrev 
## 1   CALIFORNIA   california  CA 
## 2    ARIZONA    arizona  AZ 
## 3    ARKANSAS    arkansas  AR 
## 4    colorado    colorado  CO 
## 5   CONNECTICUT   connecticut  CT 
## 6 DISTRICT OF COLUMBIA district of columbia <NA> 
## 7    FLORIDA    florida  FL 
## 8    Georgia    georgia  GA 
## 9    hawaii    hawaii  HI 
## 10    Illinois    illinois  IL 
## 11    Indiana    indiana  IN 
## 12     Iowa     iowa  IA 
## 13    kansas    kansas  KS 
## 14    Kentucky    kentucky  KY 
## 15   LOUISIANA   louisiana  LA 
## 16    Maine    maine  ME 
## 17   Marryland   marryland <NA> 
## 18  Massachusetts  massachusetts  MA 
## 19    Michigan    michigan  MI 
## 20   Minnesota   minnesota  MN 
## 21    Missouri    missouri  MO 
## 22    MONTANA    montana  MT 
## 23    NEBRASKA    nebraska  NE 
## 24    Nevada    nevada  NV 
## 25  New Hampshire  new hampshire  NH 
## 26   New Jersey   new jersey  NJ 
## 27   NEW MEXICO   new mexico  NM 
## 28    New York    new york  NY 
## 29  North Carolina  north carolina  NC 
## 30     OHIO     ohio  OH 
## 31    OKLAHOMA    oklahoma  OK 
## 32    Oregon    oregon  OR 
## 33    palmer    palmer <NA> 
## 34    PANAMA    panama <NA> 
## 35   Pennsylvania   pennsylvania  PA 
## 36  SOUTH CAROLINA  south carolina  SC 
## 37   SOUTH DAKOTA   south dakota  SD 
## 38    Tejas    tejas <NA> 
## 39   Tennessee   tennessee  TN 
## 40    Texas    texas  TX 
## 41     TX.     tx. <NA> 
## 42     UTAH     utah  UT 
## 43  Virgin Islands  virgin islands <NA> 
## 44    VIRGINIA    virginia  VA 
## 45   Washington   washington  WA 
## 46  West Virginia  west virginia  WV 
## 47   WISCONSIN   wisconsin  WI 
## 48    Wyoming    wyoming  WY