How to Use IsoMemo for Researchers

library(IsoMemo)
getDatabaseList() # returns a character format of list of database names linked to the API call
#> [1] "14CSea"   "CIMA"     "IntChron" "LiVES"
df = getData(db="IntChron",category = "Location")
# see latitude and longitude of each site
head(df)
#>                           site
#> 1                        Semna
#> 2                        Semna
#> 3                        Kumma
#> 4 Saqqara Step Pyramid Complex
#> 5                   El-Bersheh
#> 6                        Buhen

The function below retrieves ALL data and fields from all existing databases.

# ALL_DATA = getData()
# print(nrow(ALL_DATA)) # check how many rows
# levels(ALL_DATA$source) # check all the database sources are there

Let’s explore another database: LiVES

getDatabaseList() # tells what database are currently published
#> [1] "14CSea"   "CIMA"     "IntChron" "LiVES"

df1 = getData('LiVES')
summary(df1)
#>    source           id                                description  
#>  LiVES:3664   1000   :   1   Makrigialos , S Neo (I)        :  22  
#>               1001   :   1   Ajdovska Jama , S Neo (Lengyel):  10  
#>               1002   :   1   Argus Bank , S Meso (Kongemose):   7  
#>               1003   :   1   Spathes , S BZ                 :   5  
#>               1004   :   1   Korinos , S BZ                 :   4  
#>               1005   :   1   Rymnio , S BZ                  :   4  
#>               (Other):3658   (Other)                        :3612  
#>       d13C             d15N          latitude       longitude      
#>  Min.   :-25.00   Min.   : 4.38   Min.   :32.36   Min.   :-10.439  
#>  1st Qu.:-20.65   1st Qu.: 8.60   1st Qu.:40.42   1st Qu.:  7.506  
#>  Median :-19.89   Median : 9.70   Median :48.57   Median : 13.847  
#>  Mean   :-19.66   Mean   :10.14   Mean   :47.22   Mean   : 14.921  
#>  3rd Qu.:-19.10   3rd Qu.:11.20   3rd Qu.:51.87   3rd Qu.: 22.717  
#>  Max.   :-10.27   Max.   :18.31   Max.   :68.09   Max.   : 84.050  
#>  NA's   :60       NA's   :721                                      
#>               site         dateMean        dateLower        dateUpper    
#>  Durankulak     :  83   Min.   :   686   Min.   :   758   Min.   :  352  
#>  Aghia Triada   :  70   1st Qu.:  3150   1st Qu.:  2559   1st Qu.: 2065  
#>  Aiterhofen     :  60   Median :  4495   Median :  3970   Median : 3520  
#>  Lepenski Vir   :  55   Mean   :  4970   Mean   :  4761   Mean   : 4224  
#>  Varna          :  55   3rd Qu.:  5421   3rd Qu.:  5360   3rd Qu.: 5000  
#>  Niederröblingen:  53   Max.   :105000   Max.   :130000   Max.   :80000  
#>  (Other)        :3288   NA's   :7        NA's   :7        NA's   :7      
#>  dateUncertainty         datingType  
#>  Min.   :  -17.5   expert     :2225  
#>  1st Qu.:   49.0   radiocarbon:1439  
#>  Median :   80.0                     
#>  Mean   :  125.5                     
#>  3rd Qu.:  125.0                     
#>  Max.   :12500.0                     
#>  NA's   :273

How is the distribution of the variable “d15N” isotope?

hist(df1$d15N)

Let’s see the linear relationship between variables d13C and d15N:

df1 <- na.omit(df1)
lm(d13C~d15N,data=df1)
#> 
#> Call:
#> lm(formula = d13C ~ d15N, data = df1)
#> 
#> Coefficients:
#> (Intercept)         d15N  
#>    -21.8468       0.2195