Na base R, usando merge
(pacote base
):
df1 <- read.csv(text="p1,p10,p16,p19,p25,p3,p5,p6,p8,p9
con1,567,0,3,0,18,17,8,4,6,7
con3,490,7,6,2,23,26,20,14,12,29
con4,737,1,4,1,6,4,1,4,8,5
con5,145,6,4,0,11,17,5,9,22,11
con10,68,0,0,34,4,0,0,0,0,0
con30,46,0,0,8,0,0,0,0,0,0
con2,72,0,0,8,0,1,0,0,0,0")
df2 <- read.csv(text="name,superkingdom,phylum,class,order,family,genus,species
con1,Viruses,,,,Pox,Alphaen,Ano
con30,Viruses,,,Her,Allo,Bat,Ran
con4,Viruses,,,,,,Hud
con5,Viruses,,,,Mimi,Cafe,Caf
con10,Viruses,,,,,,Hud
con2,Viruses,,,Pico,Picorn,Entero,En
con3,Viruses,,,,,Phyco,Chloro")
# by.x=0 joins df1 by rownames
merge(df1, df2, by.x=0, by.y="name")
# Row.names p1 p10 p16 p19 p25 p3 p5 p6 p8 p9 superkingdom phylum class order family genus species
# 1 con1 567 0 3 0 18 17 8 4 6 7 Viruses NA NA Pox Alphaen Ano
# 2 con10 68 0 0 34 4 0 0 0 0 0 Viruses NA NA Hud
# 3 con2 72 0 0 8 0 1 0 0 0 0 Viruses NA NA Pico Picorn Entero En
# 4 con3 490 7 6 2 23 26 20 14 12 29 Viruses NA NA Phyco Chloro
# 5 con30 46 0 0 8 0 0 0 0 0 0 Viruses NA NA Her Allo Bat Ran
# 6 con4 737 1 4 1 6 4 1 4 8 5 Viruses NA NA Hud
# 7 con5 145 6 4 0 11 17 5 9 22 11 Viruses NA NA Mimi Cafe Caf