How to create data frame from ICC output correctly
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I am trying to take the output from my ICC calculation and create a data frame (see sample data and code below). Everything appears to work perfectly when I view the new data frame, but if you use str() it reveals that all variables are factors and my results are actually factor levels with the actual data counts for each factor level. This is particularly a problem because I would like to manipulate the new data frame. 

I am relatively new to R and I cannot figure out how can I modify my code correct this problem.


Dataset:

    WW_Wing_13C_Summary <- structure(list(Individual_ID = c("WW_08A_02", "WW_08A_03",
    "WW_08A_04", "WW_08A_05", "WW_08A_06", "WW_08A_08", "WW_08A_09", "WW_08A_13", 
    "WW_08B_02", "WW_08G_01", "WW_08G_02", "WW_08G_05", "WW_08G_07", 
    "WW_08I_01", "WW_08I_03", "WW_08I_07", "WW_08I_12"), Region = c("South", 
    "South", "South", "South", "South", "South", "South", "South", 
    "South", "North", "North", "North", "North", "North", "North", 
    "North", "North"), P1 = c(-18.67, -20.06, -16.54, -20.33, -21.28, 
    -23.86, -21.3, -21.34, -20.87, -20.32, -19.35, -21.2, -21.61, 
    -18.3, -22.3, -21.6, -24.12), P2 = c(-19.16, -20.3, -15.6, -20.28, 
    -21.24, -23.95, -21.44, -24.13, -20.95, -20.02, -19.38, -21.29, 
    -21.42, -18.53, -22.2, -21.77, -24.08), P3 = c(-20.38, -21.21, 
    -16.61, -20.58, -21.22, -24, -21.49, -23.03, -20.76, -19.92, 
    -19.7, -21.85, -21.84, -19.55, -22.18, -22.17, -24), P4 = c(-20.96, 
    -22.9, -19.65, -20.8, -21.2, -24.16, -21.49, -21.77, -20.9, -20.05, 
    -19.94, -22.22, -21.68, -20.18, -22.14, -22.21, -24.2), P5 = c(-21.61, 
    -22.87, -20.98, -21.24, -21.47, -24.93, -21.1, -21.4, -21.02, 
    -20.23, -20.43, -22.34, -21.79, -20.96, -21.55, -22.24, -24.16
    ), P6 = c(-21.65, -21.13, -21.18, -20.94, -21.23, -24.93, -20.84, 
    -21.57, -20.84, -20.73, -20.08, -22.42, -21.49, -21.08, -20.85, 
    -22.47, -22.87), P7 = c(-21.31, -20.68, -21.7, -20.54, -21.89, 
    -24.48, -20.78, -21.45, -21.11, -20.91, -20.81, -22.69, -21.88, 
    -21.5, -23.1, -22.19, -22.51), P8 = c(-20.8, -20.58, -21.18, 
    -21.04, -21.89, -24.17, -21.58, -21.32, -20.64, -19.87, -20.9, 
    -22.75, -21.62, -17.42, -20.75, -21.89, -22.12), P9 = c(-21.28, 
    -20.69, -21.33, -20.42, -21.6, -23.1, -20.76, -21.59, -20.11, 
    -19.58, -19.24, -22.73, -21.54, -13.18, -20.9, -21.89, -22.3)), 
    .Names = c("Individual_ID", "Region", "P1", "P2", "P3", "P4", "P5",
    "P6", "P7", "P8", "P9"), class = "data.frame", row.names = c(NA, -17L))


Code:

    ## split the complete dataset by regions
    WW_Wing_13C_Summary_Region <- split(WW_Wing_13C_Summary, WW_Wing_13C_Summary$Region)

    library(psych)
    # calculate ICC for delta-13C and create a data frame with results
    WW_Wing_13C_ICC <- data.frame(t(sapply(WW_Wing_13C_Summary_Region,
        function(temp) unlist(ICC(temp[ , c(3:11)])[c("results", "summary")]))))[ , c(49, 52, 55, 58, 61, 9, 39, 45)]

    # View results
    WW_Wing_13C_ICC

    # View structure of dataframe
    str(WW_Wing_13C_ICC)