> D=read.csv("wideM.csv",stringsAsFactors =F)
> D[1,c(1,1001)]
    V1 year
1 John 1880
> D$V1[1]
[1] "John"
> D$year[1]
[1] 1880

...
or for females:
> D=read.csv("wideF.csv",stringsAsFactors =F)
> D[1,c(1,1001)]
    V1 year
1 Mary 1880
> D$V1[1]
[1] "Mary"
> D$year[1]
[1] 1880

Q1:
%Df[39,100] "Mattie" ; Dm[39,100] "Homer"

Q2:
1879+1=1880 the first row (no row 0)


Q3: 1879+73=1952; 1879+77=1956
> which(Dm[73,]=="Tom") [1] 181
> which(Df[77,]=="Ellen") [1] 84

Q4:
(3 in males and 120 in females)
sum(is.na(Dlong$value))

Q5:
%mL 137997, fL 137880

Q6:
plot(Dlong$year[Dlong$value=="Tom"],Dlong$key[Dlong$value=="Tom"],pch=17)