I have a tibble with two columns and 312 rows: individual and different. The column individual is an integer vector with numbers 1 to 312. The column different is a character vector with each row listing individuals that are definitely different. If an individual is not listed in different, then it could be the same individual.
Below is the first 5 individuals in the tibble. I need to find the minimum number of unique individuals. How can I do this in R?
structure(list(individual = 1:5, different = c("100,101,102,103,104,105,106,107,108,109,11,110,111,112,113,114,115,116,117,118,119,12,120,121,122,123,124,125,126,127,128,129,13,130,131,132,133,134,135,136,137,138,139,14,140,141,142,143,144,145,146,147,148,149,15,150,151,152,153,154,155,156,157,158,159,16,160,161,162,163,164,165,166,167,168,169,17,170,171,172,173,174,175,176,177,178,179,18,180,181,182,183,184,185,186,187,188,189,19,190,191,192,193,194,195,196,197,198,199,20,200,201,202,203,204,205,206,207,208,209,21,210,211,212,213,214,215,216,217,218,219,22,220,221,222,223,224,225,226,227,228,229,23,230,231,232,233,234,235,236,237,238,239,24,240,241,242,243,244,245,246,247,248,249,25,250,251,252,253,254,255,256,257,258,259,26,260,261,262,263,264,265,266,267,268,269,27,270,271,272,273,274,275,276,277,278,279,28,280,281,282,283,284,285,286,287,288,289,29,290,291,292,293,294,295,296,297,298,299,30,300,301,302,303,304,305,306,307,308,309,31,310,311,312,32,33,34,35,36,37,38,39,4,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,6,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,9,90,91,92,93,94,95,96,97,98,99,NA2,",
"100,101,102,103,104,105,106,107,108,109,11,110,111,112,113,114,115,116,117,118,119,12,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,15,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,18,180,181,182,183,184,185,186,187,188,189,19,190,191,192,193,194,195,196,197,198,199,20,200,201,202,203,204,205,206,207,208,209,21,210,211,212,213,214,215,216,217,218,219,22,220,221,222,223,224,225,226,227,228,229,23,230,231,232,233,234,235,236,237,238,239,24,240,241,242,243,244,245,246,247,248,249,25,250,251,252,253,254,255,256,257,258,259,26,260,261,262,263,264,265,266,267,268,269,27,270,271,272,273,274,275,276,277,278,279,28,280,281,282,283,284,285,286,287,288,289,29,290,291,292,293,294,295,296,297,298,299,30,300,301,302,303,304,305,306,307,308,309,31,310,311,312,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,NA4,",
"100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,19,190,191,192,193,194,195,196,197,198,199,20,200,201,202,203,204,205,206,207,208,209,21,210,211,212,213,214,215,216,217,218,219,22,220,221,222,223,224,225,226,227,228,229,23,230,231,232,233,234,235,236,237,238,239,24,240,241,242,243,244,245,246,247,248,249,25,250,251,252,253,254,255,256,257,258,259,26,260,261,262,263,264,265,266,267,268,269,27,270,271,272,273,274,275,276,277,278,279,28,280,281,282,283,284,285,286,287,288,289,29,290,291,292,293,294,295,296,297,298,299,30,300,301,302,303,304,305,306,307,308,309,31,310,311,312,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,NA,",
"100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,24,240,241,242,243,244,245,246,247,248,249,25,250,251,252,253,254,255,256,257,258,259,26,260,261,262,263,264,265,266,267,268,269,27,270,271,272,273,274,275,276,277,278,279,28,280,281,282,283,284,285,286,287,288,289,29,290,291,292,293,294,295,296,297,298,299,30,300,301,302,303,304,305,306,307,308,309,31,310,311,312,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,NA,",
"100,101,102,103,104,105,106,107,108,109,11,110,111,112,113,114,115,116,117,118,119,12,120,121,122,123,124,125,126,127,128,129,13,130,131,132,133,134,135,136,137,138,139,14,140,141,142,143,144,145,146,147,148,149,15,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,19,190,191,192,193,194,195,196,197,198,199,20,200,201,202,203,204,205,206,207,208,209,21,210,211,212,213,214,215,216,217,218,219,22,220,221,222,223,224,225,226,227,228,229,23,230,231,232,233,234,235,236,237,238,239,24,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,29,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,32,33,34,35,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,6,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,9,90,91,92,93,94,95,96,97,98,99,NA,"
)), row.names = c(NA, -5L), class = c("tbl_df", "tbl", "data.frame"
)) -> df
full_range <- 1:312
df %>%
mutate(
different_list = str_split(different, ",") %>%
map(~ as.integer(str_trim(.))),
same = map(different_list, ~ setdiff(full_range, .))
) %>%
dplyr::select(-different_list) ->
df_with_same