How to extract a vector by 100+ unique character strings without having to type all of them by hand in R -
i have data set of more 86,000 different rows , 27 variables. list of different individuals, company, percentage attendance, among other things. each company has data 2010-2011 starting in september way 2015-2016.
a portion of data set below omissions , ellipses indicate transitions.
yr company month mo % attendance %change 2010-11 "015jk" 1 sep 88.21 2010-11 "015jk" 2 oct 92.51 4.31 2010-11 "015jk" 3 nov 90.97 -1.54 2010-11 "015jk" 4 dec 89.19 -1.78 2010-11 "015jk" 5 jan 86.88 -2.31 2010-11 "015jk" 6 feb 89.28 2.4
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yr company month mo % attendance %change 2015-2016 015jk 1 jan 82 2015-2016 015jk 2 feb 64 -18 2015-2016 015jk 3 mar 94 30 2015-2016 015jk 4 april 98 4 2015-2016 015jk 5 may 50 -48 2015-2016 015jk 6 june 68 18
this typical set of data whereupon start again time start new company such:
yr company month mo %attendance %change 2010-2011 0184jk 1 jan 49 2010-2011 0184jk 2 feb 52 3 2010-2011 0184jk 3 mar 82 30 2010-2011 0184jk 4 april 55 -27 2010-2011 0184jk 5 may 53 -2 2010-2011 0184jk 6 june 80 27
...
yr company month mo %attendance %change 2015-2016 0184jk 1 jan 87 2015-2016 0184jk 2 feb 47 -40 2015-2016 0184jk 3 mar 61 14 2015-2016 0184jk 4 april 78 17 2015-2016 0184jk 5 may 43 -35 2015-2016 0184jk 6 june 85 42
i can capture these sets of data relatively massive 86,000 row datasheet following r codes
015jk <- df[ which( df$company== "015j"), ] 0184jk <- df[ which( df$company== "0184jk"), ]
the problem that have more 100 plus companies , onerous type in 90+ iterations of
some company name such 015jk <-df[ which(df$company== "some company name"), ]
is there way extract unique values of company , input multiple iterations of following aforementioned variety:
some company code name such 015jk <-df[ which(df$company== "some company code"), ]
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