Объединить две таблицы на основе значения в первом столбце

У меня есть 1 таблица, как это (CSV-файл):

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 

И вторая таблица (CSV-файл):

 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 

Я хочу скопировать в первую таблицу столбцы (2: 8) из второй таблицы, все на основе того же значения в первом столбце.

Пример вывода

  p1 p10 p16 p19 p25 p3 p5 p6 p8 p9 superkingdom phylum class order family genus species con1 567 0 3 0 18 17 8 4 6 7 Viruses Pox Alphaen Ano con3 490 7 6 2 23 26 20 14 12 29 Viruses Phyco Chloro con4 737 1 4 1 6 4 1 4 8 5 Viruses Hud con5 145 6 4 0 11 17 5 9 22 11 Viruses Mimi Cafe Caf con10 68 0 0 34 4 0 0 0 0 0 Viruses Hud con30 46 0 0 8 0 0 0 0 0 0 Viruses Her Allo Bat Ran con2 72 0 0 8 0 1 0 0 0 0 Viruses Pico Picorn Entero En 

В базе R, используя merge (пакет 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