Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Selected Reading
How to find the position of minimum value in a vector that contains integers as strings in R?
If integer vector is read as strings and we want to find the position of the minimum value in that vector then we need to use as.numeric along with the vector to read it as a numeric vector then use which function for finding the position of the minimum value. For example, if we have a vector x that contains first ten integers as strings then to find the position of the minimum we can use which(as.numeric(x)==min(as.numeric(x))).
Example1
x1<−c("1","2","3","4")
which(as.numeric(x1)==min(as.numeric(x1)))
[1] 1
Example2
x2<−sample(c("18","22","13","14","25","8","17"),120,replace=TRUE)
x2
[1] "17" "25" "25" "8" "8" "25" "22" "18" "14" "17" "17" "13" "13" "18" "17"
[16] "25" "8" "14" "17" "25" "22" "13" "18" "18" "22" "18" "25" "18" "17" "22"
[31] "18" "18" "14" "17" "8" "22" "17" "25" "13" "14" "18" "18" "8" "17" "14"
[46] "14" "8" "22" "8" "14" "18" "25" "14" "18" "18" "18" "14" "25" "18" "13"
[61] "18" "22" "25" "13" "22" "14" "14" "17" "8" "17" "18" "18" "22" "17" "18"
[76] "13" "18" "13" "25" "18" "8" "22" "8" "17" "13" "22" "22" "14" "25" "8"
[91] "18" "17" "13" "8" "14" "17" "13" "13" "14" "14" "13" "14" "8" "17" "8"
[106] "17" "22" "25" "25" "8" "8" "22" "13" "18" "18" "25" "8" "8" "17" "17"
which(as.numeric(x2)==min(as.numeric(x2)))
[1] 4 5 17 35 43 47 49 69 81 83 90 94 103 105 110 111 117 118
Example3
x3<−sample(c("118","322","413","214","125","418","317","247","258","320"),120,replace=TRUE)
x3
[1] "320" "317" "118" "418" "413" "413" "214" "247" "247" "317" "258" "258"
[13] "247" "317" "247" "214" "125" "125" "413" "247" "320" "320" "258" "214"
[25] "322" "125" "320" "118" "125" "317" "322" "322" "320" "317" "118" "322"
[37] "320" "247" "418" "214" "258" "418" "322" "317" "258" "118" "247" "118"
[49] "320" "258" "247" "320" "258" "118" "418" "413" "214" "247" "418" "413"
[61] "214" "320" "320" "118" "214" "413" "418" "418" "317" "320" "118" "247"
[73] "247" "214" "125" "317" "214" "247" "322" "413" "125" "322" "125" "258"
[85] "418" "320" "317" "258" "214" "320" "118" "413" "317" "418" "118" "320"
[97] "247" "317" "317" "413" "247" "320" "413" "317" "413" "320" "320" "258"
[109] "322" "413" "320" "214" "247" "214" "125" "320" "317" "118" "125" "322"
which(as.numeric(x3)==min(as.numeric(x3)))
[1] 3 28 35 46 48 54 64 71 91 95 118
Example4
x4<−sample(c("518","309","213","235","325","328","317","247","358","420","299","500"),120,replace=TRUE)
x4
[1] "420" "328" "247" "500" "500" "358" "317" "500" "317" "235" "358" "317"
[13] "317" "247" "235" "247" "299" "358" "518" "213" "325" "299" "317" "309"
[25] "235" "299" "317" "518" "247" "309" "328" "317" "500" "358" "328" "299"
[37] "309" "358" "235" "420" "325" "328" "299" "500" "299" "317" "328" "309"
[49] "299" "420" "247" "235" "358" "235" "358" "500" "518" "328" "325" "420"
[61] "309" "213" "328" "420" "213" "213" "518" "317" "299" "213" "235" "309"
[73] "420" "299" "358" "213" "325" "325" "420" "235" "358" "500" "500" "328"
[85] "247" "213" "309" "420" "213" "518" "328" "420" "420" "500" "213" "358"
[97] "518" "213" "358" "247" "235" "299" "247" "500" "309" "317" "420" "420"
[109] "317" "213" "500" "420" "309" "500" "309" "309" "213" "328" "213" "518"
which(as.numeric(x4)==min(as.numeric(x4)))
[1] 20 62 65 66 70 76 86 89 95 98 110 117 119
Example5
x5<−sample(c("5112","2542","3241","3211","4125","2568","3742","2784","4269","3627"),120,replace=TRUE)
x5
[1] "3211" "4125" "2784" "5112" "3211" "3742" "4269" "2542" "3742" "2568"
[11] "2568" "2568" "2784" "2784" "3742" "3742" "2542" "5112" "2542" "5112"
[21] "5112" "3211" "3627" "4125" "3742" "5112" "2542" "2568" "2542" "3742"
[31] "3211" "2542" "2568" "3241" "4125" "3211" "3742" "2568" "3742" "4125"
[41] "3241" "3211" "3241" "4269" "4269" "2784" "2784" "3627" "2568" "2542"
[51] "2542" "2784" "2542" "2568" "2542" "4125" "2542" "2568" "3627" "5112"
[61] "2784" "2568" "4125" "2568" "4125" "3211" "2568" "2784" "3627" "2784"
[71] "3742" "5112" "2568" "2542" "4125" "5112" "4125" "3211" "4269" "3742"
[81] "3627" "2568" "2784" "5112" "2784" "3211" "3627" "2542" "3627" "4269"
[91] "3742" "2542" "2542" "4269" "3211" "2784" "3742" "2568" "3627" "3742"
[101] "3742" "4125" "2784" "2784" "4125" "3742" "3627" "3627" "3241" "4125"
[111] "4125" "2784" "5112" "2542" "3627" "5112" "3241" "3742" "2568" "2784"
which(as.numeric(x5)==min(as.numeric(x5)))
[1] 8 17 19 27 29 32 50 51 53 55 57 74 88 92 93 114 Advertisements
