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))
现在我要做的是为不同的储蓄类型获取单独的累积总和表。这就是我想要NPI Efficiencie，制造Excel和材料效率的单独累积总和表。无论如何我可以在R的帮助下做到这一点。请帮忙！
答案 0 :(得分：0)
喜欢这个吗？
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]