R 我们应该如何获得不同类型变量的累积列？

我的数据是这样的：

structure(c("Manufacturing Excell", "NPI Efficiencies", "NPI Efficiencies", 
"Manufacturing Excell", "Manufacturing Excell", "Material Efficiencie", 
"NPI Efficiencies", "Manufacturing Excell", "NPI Efficiencies", 
"NPI Efficiencies", "NPI Efficiencies", "Material Efficiencie", 
"NPI Efficiencies", "NPI Efficiencies", "Manufacturing Excell", 
"Manufacturing Excell", "NPI Efficiencies", "NPI Efficiencies", 
"NPI Efficiencies", "NPI Efficiencies", "Material Efficiencie", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "Manufacturing Excell", 
"NPI Efficiencies", "NPI Efficiencies", "Manufacturing Excell", 
"Manufacturing Excell", "Manufacturing Excell", "Manufacturing Excell", 
"NPI Efficiencies", "Manufacturing Excell", "Material Efficiencie", 
"Manufacturing Excell", "Manufacturing Excell", "NPI Efficiencies", 
"Manufacturing Excell", "Manufacturing Excell", "Manufacturing Excell", 
"NPI Efficiencies", "NPI Efficiencies", "Material Efficiencie", 
"NPI Efficiencies", "Manufacturing Excell", "NPI Efficiencies", 
"Manufacturing Excell", "NPI Efficiencies", "Manufacturing Excell", 
"Manufacturing Excell", "Manufacturing Excell", "NPI Efficiencies", 
"NPI Efficiencies", "Manufacturing Excell", "NPI Efficiencies", 
"NPI Efficiencies", "Manufacturing Excell", "Manufacturing Excell", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "Material Efficiencie", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", 
"Manufacturing Excell", "Manufacturing Excell", "Material Efficiencie", 
"NPI Efficiencies", "NPI Efficiencies", "Material Efficiencie", 
"Material Efficiencie", "NPI Efficiencies", "NPI Efficiencies", 
"Manufacturing Excell", "NPI Efficiencies", "NPI Efficiencies", 
"NPI Efficiencies", "Material Efficiencie", "NPI Efficiencies", 
"Material Efficiencie", "Manufacturing Excell", "Material Efficiencie", 
"NPI Efficiencies", "Manufacturing Excell", "Material Efficiencie", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "Manufacturing Excell", 
"Manufacturing Excell", "NPI Efficiencies", "Manufacturing Excell", 
"Material Efficiencie", "NPI Efficiencies", "Material Efficiencie", 
"NPI Efficiencies", "NPI Efficiencies", "Manufacturing Excell", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", 
"Manufacturing Excell", "Material Efficiencie", "Material Efficiencie", 
"Manufacturing Excell", "Material Efficiencie", "Manufacturing Excell", 
"Manufacturing Excell", "NPI Efficiencies", "NPI Efficiencies", 
"NPI Efficiencies", "Manufacturing Excell", "Material Efficiencie", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "Manufacturing Excell", 
"Manufacturing Excell", "NPI Efficiencies", "NPI Efficiencies", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "Manufacturing Excell", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", 
"Manufacturing Excell", "NPI Efficiencies", "Manufacturing Excell", 
"NPI Efficiencies", "Material Efficiencie", "NPI Efficiencies", 
"NPI Efficiencies", "Manufacturing Excell", "Manufacturing Excell", 
"Manufacturing Excell", "NPI Efficiencies", "NPI Efficiencies", 
"Material Efficiencie", "Material Efficiencie", "Material Efficiencie", 
"Material Efficiencie", "NPI Efficiencies", "NPI Efficiencies", 
"Manufacturing Excell", "Manufacturing Excell", "Manufacturing Excell", 
"Manufacturing Excell", "Manufacturing Excell", "Manufacturing Excell", 
"NPI Efficiencies", "NPI Efficiencies", "NPI Efficiencies", "Manufacturing Excell", 
"Manufacturing Excell", "Material Efficiencie", "NPI Efficiencies", 
"NPI Efficiencies", "28859", "15134", "29429", "14214", "37988", 
"15328", "42679", "46206", "43311", "8158", "29937", "6021", 
"5581", "44627", "36779", "15888", "20088", "42170", "11560", 
"16401", "30293", "27682", "44574", "20240", "10176", "45920", 
"40615", "28510", "23527", "35717", "12608", "30585", "1344", 
"30179", "38589", "18135", "32662", "577", "47836", "36944", 
"8946", "36730", "6499", "47177", "31564", "17612", "19799", 
"43469", "780", "29003", "729", "39209", "8237", "12442", "40877", 
"45338", "44977", "2081", "47886", "19948", "38960", "27127", 
"33186", "36972", "29774", "24197", "47513", "21171", "10992", 
"2630", "39740", "38639", "8373", "7932", "44641", "8877", "4256", 
"47425", "4972", "11793", "48437", "15102", "30181", "23058", 
"27086", "11750", "32797", "33320", "42980", "2712", "3360", 
"18773", "34625", "48207", "18044", "16727", "36327", "38051", 
"39081", "35858", "11747", "32221", "45342", "25444", "27538", 
"3725", "29636", "37667", "24387", "43088", "49972", "39308", 
"17497", "26198", "42199", "20640", "26455", "42792", "36511", 
"16867", "34142", "10629", "15415", "38989", "24381", "45988", 
"19603", "40886", "16616", "13004", "8370", "34725", "17915", 
"29838", "38500", "10620", "45602", "11911", "38119", "308", 
"37473", "17560", "14887", "30872", "7622", "20169", "38494", 
"12728", "14816", "37183", "18602", "157", "49615", "12902", 
"31344", "15606", "30386", "49746", "26466", "19784", "9326", 
"33639", "25323", "31404", "20045", "45788", "49454", "13271", 
"44675", "44926", "33041"), .Dim = c(171L, 2L))

现在我想做的是为不同的储蓄类型得到一个单独的累计总和表。也就是说，我想要一个单独的累积总和表，用于NPI效率、制造Excel和材料效率。在R的帮助下，我有什么办法可以做到这一点。请帮忙

像这样

library(dplyr)
library(data.table)
dt <- data.frame(dt) %>% setDT
dt[, X2 := as.character(X2) %>% as.numeric]
dt[, cumsum_by_group := cumsum(X2), by = X1]

你有一个字符类的矩阵。