Question

我有一个包含4列的data.frame。第2列具有每个人的唯一ID（＆＃34; Cofecha＆＃34;），第4列具有给定个人所属的图（＆＃34; Plot＆＃34;）。 data.frame中每个人都有多次出现。我试图做两件事：（1）获得独特个体的数量，然后（2）找出每个情节中有多少独特个体出现。我可以找到总独特个体的数量（摘录中有4个），但我无法弄清楚如何计算每个情节的个体数量。任何帮助将不胜感激！

摘自原始data.frame：

dx1＆lt; - structure（list（Year = c（1920L，1921L，1921L，1922L，1922L，1923L， 1923L，1924L，1924L，1924L，1925L，1925L，1925L，1926L，1926L， 1926L，1927L，1927L，1927L，1927L，1928L，1928L，1928L，1928L， 1929L），Cofecha =结构（c（69L，166L，69L，166L，69L，166L， 69L，166L，69L，50L，166L，69L，50L，166L，69L，50L，166L，232L， 69L，50L，166L，232L，69L，50L，166L）,.标签= c（＆＃34; LB1A002＆＃34;，＆＃34; LB1A003＆＃34;，＆＃34; LB1A101＆＃34;，＆＃34; LB1A102＆＃34;，＆＃34; LB1A103＆＃34;，＆＃34; LB1A212＆＃34;，＆＃34; LB1A228＆＃34 ;, ＆＃34; LB1A231＆＃34;，＆＃34; LB1A233＆＃34;，＆＃34; LB1B001＆＃34;，＆＃34; LB1B002＆＃34;，＆＃34; LB1B003＆＃34;，＆＃34; LB1B210＆＃34 ;, ＆＃34; LB1B216＆＃34;，＆＃34; LB2A001＆＃34;，＆＃34; LB2A002＆＃34;，＆＃34; LB2A003＆＃34;，＆＃34; LB2A004＆＃34;，＆＃34; LB2A008＆＃34 ;, ＆＃34; LB2A009＆＃34;，＆＃34; LB2A011＆＃34;，＆＃34; LB2B001＆＃34;，＆＃34; LB2B005＆＃34;，＆＃34; LB2B008＆＃34;，＆＃34; LB2B101＆＃34 ;, ＆＃34; LB2B102＆＃34;，＆＃34; LB2B103＆＃34;，＆＃34; LB2C003＆＃34;，＆＃34; LB2C004＆＃34;，＆＃34; LB2C008＆＃34;，＆＃34; LB2C009＆＃34 ;, ＆＃34; LB2C010＆＃34;，＆＃34; LB2C001＆＃34;，＆＃34; LB2D005＆＃34;，＆＃34; LB2D006＆＃34;，＆＃34; LB2D007＆＃34;，＆＃34; LB2D008＆＃34 ;, ＆＃34; LB2D009＆＃34;，＆＃34; LB2D010＆＃34;，＆＃34; LB2D101＆＃34;，＆＃34; SM1A005＆＃34;，＆＃34; SM1A101＆＃34;，＆＃34; SM1A301＆＃34 ;, ＆＃34; SM1A302＆＃34;，＆＃34; SM1B003＆＃34;，＆＃34; SM1C005＆＃34;，＆＃34; SM1C302＆＃34;，＆＃34; SM1D006＆＃34;，＆＃34; SM2A004＆＃34 ;, ＆＃34; SM2A005＆＃34;，＆＃34; SM2A007＆＃34;，＆＃34; SM2A210＆＃34;，＆＃34; SM2A301＆＃34;，＆＃34; SM2B001＆＃34;，＆＃34; SM2B005＆＃34 ;, ＆＃34; SM2B006＆＃34;，＆＃34; SM2B101＆＃34;，＆＃34; SM2C005＆＃34;，＆＃34; SM2C101＆＃34;，＆＃34; SM2C301＆＃34;，＆＃34; SM2D006＆＃34 ;, ＆＃34; SM2D101＆＃34;，＆＃34; SM2D221＆＃34;，＆＃34; IR1A004＆＃34;，＆＃34; IR1A009＆＃34;，＆＃34; IR1A206＆＃34;，＆＃34; IR1B001＆＃34 ;, ＆＃34; IR1B004＆＃34;，＆＃34; IR1B005＆＃34;，＆＃34; IR1B301＆＃34;，＆＃34; IR1B302＆＃34;，＆＃34; IR1C005＆＃34;，＆＃34; IR1C006＆＃34 ;, ＆＃34; IR1C007＆＃34;，＆＃34; IR1C008＆＃34;，＆＃34; IR1C204＆＃34;，＆＃34; IR1C205＆＃34;，＆＃34; IR1D002＆＃34;，＆＃34; IR1D101＆＃34 ;, ＆＃34; IR2A003＆＃34;，＆＃34; IR2A101＆＃34;，＆＃34; IR2A211＆＃34;，＆＃34; IR2A234＆＃34;，＆＃34; IR2B002＆＃34;，＆＃34; IR2B005＆＃34 ;, ＆＃34; IR2B101＆＃34;，＆＃34; IR2B201＆＃34;，＆＃34; IR2B210＆＃34;，＆＃34; IR2B229＆＃34;，＆＃34; IR2C230＆＃34;，＆＃34; IR2C256＆＃34 ;, ＆＃34; IR2C301＆＃34;，＆＃34; IR2C302＆＃34;，＆＃34; IR2C002＆＃34;，＆＃34; IR2C009＆＃34;，＆＃34; IR2C101＆＃34;，＆＃34; IR2C204＆＃34 ;, ＆＃34; IR2C215＆＃34;，＆＃34; IR2D227＆＃34;，＆＃34; IR2D228＆＃34;，＆＃34; IR2D237＆＃34;，＆＃34; IR2D254＆＃34;，＆＃34; IR2D301＆＃34 ;, ＆＃34; IR2D302＆＃34;，＆＃34; IR2D003＆＃34;，＆＃34; IR2D006＆＃34;，＆＃34; IR2D009＆＃34;，＆＃34; IR2D011＆＃34;，＆＃34; IR2D207＆＃34 ;, ＆＃34; IR2D216＆＃34;，＆＃34; JA1A101＆＃34;，＆＃34; JA1A224＆＃34;，＆＃34; JA1A301＆＃34;，＆＃34; JA1B004＆＃34;，＆＃34; JA1B101＆＃34 ;, ＆＃34; JA1B102＆＃34;，＆＃34; JA1B219＆＃34;，＆＃34; JA1B233＆＃34;，＆＃34; JA1C002＆＃34;，＆＃34; JA1C232＆＃34;，＆＃34; JA1D001＆＃34 ;, ＆＃34; JA1D101＆＃34;，＆＃34; JA2A101＆＃34;，＆＃34; JA2A102＆＃34;，＆＃34; JA2A206＆＃34;，＆＃34; JA2A209＆＃34;，＆＃34; JA2A210＆＃34 ;, ＆＃34; JA2A004＆＃34;，＆＃34; JA2A005＆＃34;，＆＃34; JA2A006＆＃34;，＆＃34; JA2A007＆＃34;，＆＃34; JA2A008＆＃34;，＆＃34; JA2B005＆＃34 ;, ＆＃34; JA2B206＆＃34;，＆＃34; JA2C001＆＃34;，＆＃34; JA2C002＆＃34;，＆＃34; JA2C007＆＃34;，＆＃34; JA2C101＆＃34;，＆＃34; JA2C202＆＃34 ;, ＆＃34; JA3N007＆＃34;，＆＃34; JA3N008＆＃34;，＆＃34; JA3N009＆＃34;，＆＃34; JA3N010＆＃34;，＆＃34; JA3N011＆＃34;，＆＃34; JA3N012＆＃34 ;, ＆＃34; JA3N001＆＃34;，＆＃34; JA3N002＆＃34;，＆＃34; JA3N003＆＃34;，＆＃34; JA3N004＆＃34;，＆＃34; JA3N005＆＃34;，＆＃34; JA3N006＆＃34 ;, ＆＃34; SF5A007＆＃34;，＆＃34; SF5B223＆＃34;，＆＃34; SF5B227＆＃34;，＆＃34; SF5B228＆＃34;，＆＃34; SF5B301＆＃34;，＆＃34; SF5B302＆＃34 ;, ＆＃34; SF5C201＆＃34;，＆＃34; SF5C214＆＃34;，＆＃34; SF5C216＆＃34;，＆＃34; SF5C301＆＃34;，＆＃34; SF5C303＆＃34;，＆＃34; SF5D004＆＃34 ;, ＆＃34; SF5D101＆＃34;，＆＃34; SF5D207＆＃34;，＆＃34; AP1A001＆＃34;，＆＃34; AP1A004＆＃34;，＆＃34; AP1A005＆＃34;，＆＃34; AP1A006＆＃34 ;, ＆＃34; AP1A008＆＃34;，＆＃34; AP1A009＆＃34;，＆＃34; AP1A010＆＃34;，＆＃34; AP1A101＆＃34;，＆＃34; AP1B005＆＃34;，＆＃34; AP1B007＆＃34 ;, ＆＃34; AP1B011＆＃34;，＆＃34; AP1B101＆＃34;，＆＃34; AP1B102＆＃34;，＆＃34; AP1C006＆＃34;，＆＃34; AP1C007＆＃34;，＆＃34; AP1C010＆＃34 ;, ＆＃34; AP1C011＆＃34;，＆＃34; AP1C001＆＃34;，＆＃34; AP1C002＆＃34;，＆＃34; AP1D001＆＃34;，＆＃34; AP1D005＆＃34;，＆＃34; AP1D007＆＃34 ;, ＆＃34; AP1D008＆＃34;，＆＃34; AP1D009＆＃34;，＆＃34; AP1D010＆＃34;，＆＃34; AP1D011＆＃34;，＆＃34; AP1D012＆＃34;，＆＃34; AP1D013＆＃34 ;, ＆＃34; AP1D101＆＃34;，＆＃34; AP1D102＆＃34;，＆＃34; AP1D103＆＃34;，＆＃34; AP1D104＆＃34;，＆＃34; AP1C004＆＃34;，＆＃34; AP1C005＆＃34 ;, ＆＃34; AP2A001＆＃34;，＆＃34; AP2A002＆＃34;，＆＃34; AP2A003＆＃34;，＆＃34; AP2B001＆＃34;，＆＃34; AP2B003＆＃34;，＆＃34; AP2B004＆＃34 ;, ＆＃34; AP2B101＆＃34;，＆＃34; AP2B102＆＃34;，＆＃34; AP2C001＆＃34;，＆＃34; AP2C002＆＃34;，＆＃34; AP2C003＆＃34;，＆＃34; AP2C004＆＃34 ;, ＆＃34; AP2C005＆＃34;，＆＃34; AP2C007＆＃34;，＆＃34; AP2C008＆＃34;，＆＃34; AP2C102＆＃34;，＆＃34; AP2C103＆＃34;，＆＃34; AP2C104＆＃34 ;, ＆＃34; AP2D001＆＃34;，＆＃34; AP2D002＆＃34;，＆＃34; AP2D005＆＃34;，＆＃34; AP2D006＆＃34;，＆＃34; AP2D009＆＃34;，＆＃34; AP2D101＆＃34 ;, ＆＃34; AP2D102＆＃34;，＆＃34; AP2D103＆＃34;，＆＃34; AP3A003＆＃34;，＆＃34; AP3A005＆＃34;，＆＃34; AP3A008＆＃34;，＆＃34; AP3A014＆＃34 ;, ＆＃34; AP3A015＆＃34;，＆＃34; AP3A101＆＃34;，＆＃34; AP3A102＆＃34;，＆＃34; AP3B101＆＃34;，＆＃34; AP3B102＆＃34;，＆＃34; AP3B103＆＃34 ;, ＆＃34; AP3B104＆＃34;，＆＃34; AP3B003＆＃34;，＆＃34; AP3B007＆＃34;，＆＃34; AP3B010＆＃34;，＆＃34; AP3B012＆＃34;，＆＃34; AP3C003＆＃34 ;, ＆＃34; AP3C004＆＃34;，＆＃34; AP3C006＆＃34;，＆＃34; AP3C007＆＃34;，＆＃34; AP3C009＆＃34;，＆＃34; AP3C011＆＃34;，＆＃34; AP3C101＆＃34 ;, ＆＃34; AP3C102＆＃34;，＆＃34; AP3C103＆＃34;，＆＃34; AP3C104＆＃34;，＆＃34; AP3C105＆＃34;，＆＃34; AP3D006＆＃34;，＆＃34; AP3D011＆＃34 ;, ＆＃34; AP3D101＆＃34;，＆＃34; AP3D102＆＃34;，＆＃34; BF1A101＆＃34;，＆＃34; BF1A102＆＃34;，＆＃34; BF1A103＆＃34;，＆＃34; BF1A104＆＃34 ;, ＆＃34; BF1B003＆＃34;，＆＃34; BF1B005＆＃34;，＆＃34; BF1B006＆＃34;，＆＃34; BF1B007＆＃34;，＆＃34; BF1B101＆＃34;，＆＃34; BF1C007＆＃34 ;, ＆＃34; BF1C101＆＃34;，＆＃34; BF1C102＆＃34;，＆＃34; BF1D003＆＃34;，＆＃34; BF1D007＆＃34;，＆＃34; BF1D010＆＃34;，＆＃34; BF1D101＆＃34 ;, ＆＃34; BF1D102＆＃34;，＆＃34; BF1D103＆＃34;，＆＃34; BF1D210＆＃34;，＆＃34; BF2A001＆＃34;，＆＃34; BF2A002＆＃34;，＆＃34; BF2B001＆＃34 ;, ＆＃34; BF2B214＆＃34;，＆＃34; BF2B219＆＃34;，＆＃34; BF2C001＆＃34;，＆＃34; BF2C004＆＃34;，＆＃34; BF2C008＆＃34;，＆＃34; BF2C101＆＃34 ;, ＆＃34; BF2C102＆＃34;，＆＃34; BF2C201＆＃34;，＆＃34; BF2C205＆＃34;，＆＃34; BF2C213＆＃34;，＆＃34; BF2C219＆＃34;，＆＃34; BF2C301＆＃34 ;, ＆＃34; BF2D004＆＃34;，＆＃34; BF2D013＆＃34;，＆＃34; BF2D014＆＃34;，＆＃34; BF2D015＆＃34;，＆＃34; BF3A001＆＃34;，＆＃34; BF3A002＆＃34 ;, ＆＃34; BF3A004＆＃34;，＆＃34; BF3A005＆＃34;，＆＃34; BF3A007＆＃34;，＆＃34; BF3A008＆＃34;，＆＃34; BF3A009＆＃34;，＆＃34; BF3A101＆＃34 ;, ＆＃34; BF3B003＆＃34;，＆＃34; BF3B101＆＃34;，＆＃34; BF3C002＆＃34;，＆＃34; BF3C003＆＃34;，＆＃34; BF3C007＆＃34;，＆＃34; BF3C009＆＃34 ;, ＆＃34; BF3C010＆＃34;，＆＃34; BF3D002＆＃34;，＆＃34; BF3D003＆＃34;，＆＃34; BF3D004＆＃34;，＆＃34; BF3D009＆＃34;，＆＃34; BF3D010＆＃34; ），class =＆＃34; factor＆＃34;），AvgBaiTenyr = c（3.1292,2.3011,3.07395， 2.374,3.4236,2.34095,3.50005,2.3903,3.68825,2.2265,2.3547575， 3.69255,2.3487,2.417,3.57705,2.32715,2.39665,2.6338,3.433， 2.2573,2.37235,2.6384,3.496335,2.28685,2.26055），Plot = c（＆＃34; IR1＆＃34;，＆＃34; AP1＆＃34;，＆＃34; IR1＆＃34;，＆＃34; AP1＆＃34;，＆＃34; IR1＆＃34;，＆＃34; AP1＆＃34;，＆＃34; IR1＆＃34;，＆＃34; AP1＆＃34;，＆＃34; IR1＆＃34;，＆＃34; SM2＆＃34;，＆＃34; AP1＆＃34;，＆＃34; IR1＆＃34;，＆＃34; SM2＆＃34;，＆＃34; AP1＆＃34;，＆＃34; IR1＆＃34;，＆＃34; SM2＆＃34;，＆＃34; AP1＆＃34;，＆＃34; AP3＆＃34;，＆＃34; IR1＆＃34;，＆＃34; SM2＆＃34;，＆＃34; AP1＆＃34;，＆＃34; AP3＆＃34;，＆＃34; IR1＆＃34;，＆＃34; SM2＆＃34;，＆＃34; AP1＆＃34;））,. Name = c（＆＃34;年＆＃34;，＆＃34; Cofecha＆＃34;，＆＃34; AvgBaiTenyr＆＃34;，＆＃34; Plot＆＃34;），row.names = c（323L，326L， 331L，335L，341L，345L，351L，355L，361L，365L，366L，372L，376L， 377L，383L，387L，388L，391L，396L，400L，401L，404L，409L，413L， 414L），class =＆＃34; data.frame＆＃34;）

用于查找独特个体的代码：

dx2＆lt; - （unique（dx1 $ Cofecha））

我也试过＆＃34; table＆＃34;但它只给了我每个人出现多少次的计数，而不是每个情节发生了多少独特个体：

表（DX1 $ Cofecha）

有没有办法根据名字的前3个字符计算每个人？前3个字符相当于绘图ID。

Answer 1

你可以尝试

with(dx1, tapply(as.character(Cofecha), list(Plot), FUN=function(x) length(unique(x))))
#    AP1 AP3 IR1 SM2 
#     1   1   1   1

或者

library(data.table)
setDT(dx1)[, list(UniqueIDs= length(unique(Cofecha))), by=Plot]
#      Plot UniqueIDs
#   1:  IR1         1
#   2:  AP1         1
#   3:  SM2         1
#   4:  AP3         1

Answer 2

使用子字符串：

table(substr(dx1$Cofecha, 1,3))

给了我

AP1 AP3 IR1 SM2 
  9   2   9   5

用独特的方式计算每一次：

table(substr(unique(dx1$Cofecha), 1,3))
# AP1 AP3 IR1 SM2 
#   1   1   1   1

Answer 3

这是另一种方法：

library(dplyr)
dx1 %>%
  group_by(Plot) %>%
  summarize(distint_IDs = n_distinct(Cofecha))

#Source: local data frame [4 x 2]
#
#  Plot distint_IDs
#1  AP1           1
#2  AP3           1
#3  IR1           1
#4  SM2           1

还有一种使用基础R的可能性：

unlist(lapply(split(dx1, dx1$Plot), function(x) length(unique(x$Cofecha))))
#AP1 AP3 IR1 SM2 
#  1   1   1   1

R唯一值计数

3 个答案: