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How to apply multiple AND conditions to a data frame in R?
To apply multiple conditions to a data frame, we can use double and sign that is &&. For example, if we have a data frame called df that contains three columns say x, y, z and we want to add a value to all columns if first element in z equals to 5 then it can be done by using the command −
if(df$x && df$y && df$y == 5){
df$x = df$x+10
df$y = df$y+10
df$z = df$z+10
}Example1
Consider the below data frame −
x1<-rpois(20,1) x2<-rpois(20,5) x3<-rpois(20,5) df1<-data.frame(x1,x2,x3) df1
Output
x1 x2 x3 1 1 4 5 2 0 6 2 3 0 3 6 4 0 3 8 5 0 11 10 6 1 5 3 7 2 9 8 8 0 6 10 9 0 5 6 10 3 2 7 11 2 6 5 12 1 6 7 13 1 8 5 14 1 3 6 15 1 3 4 16 6 4 7 17 1 2 3 18 2 4 5 19 4 5 5 20 0 4 4
Adding 10 to each column of df1 if first element in column 3 is equal to 5 −
if(df1$x1 && df1$x2 && df1$x3 == 5){
+ df1$x1=df1$x1+10
+ df1$x2=df1$x2+10
+ df1$x3=df1$x3+10
+ }
df1x1 x2 x3 1 11 14 15 2 10 16 12 3 10 13 16 4 10 13 18 5 10 21 20 6 11 15 13 7 12 19 18 8 10 16 20 9 10 15 16 10 13 12 17 11 12 16 15 12 11 16 17 13 11 18 15 14 11 13 16 15 11 13 14 16 16 14 17 17 11 12 13 18 12 14 15 19 14 15 15 20 10 14 14
Example2
y1<-rnorm(20) y2<-rnorm(20) df2<-data.frame(y1,y2) df2
Output
y1 y2 1 -0.60985060 -1.45276610 2 0.80395413 2.06049252 3 -0.12743614 -1.03176509 4 0.05681372 1.56884539 5 -1.05750863 0.23016019 6 -0.23227935 -0.60140044 7 0.85412909 -0.85129323 8 -1.10052209 0.52922611 9 -0.97370660 1.08355421 10 -0.29749358 -0.04810183 11 1.50965424 0.29086647 12 0.11498843 -1.42433231 13 1.95463083 -0.94930405 14 -0.12241118 0.68882049 15 2.11266281 -0.70163806 16 -2.79657925 -1.17756299 17 -0.39618443 -1.60277178 18 -2.38109125 0.25505674 19 -0.84519632 0.39521130 20 0.46643806 0.04849672
if(df2$y1 && df2$y2 == 2){
+ df2$y1=df2$y1+10
+ df2$y2=df2$y2+10
+ }
df2y1 y2 1 -0.60985060 -1.45276610 2 0.80395413 2.06049252 3 -0.12743614 -1.03176509 4 0.05681372 1.56884539 5 -1.05750863 0.23016019 6 -0.23227935 -0.60140044 7 0.85412909 -0.85129323 8 -1.10052209 0.52922611 9 -0.97370660 1.08355421 10 -0.29749358 -0.04810183 11 1.50965424 0.29086647 12 0.11498843 -1.42433231 13 1.95463083 -0.94930405 14 -0.12241118 0.68882049 15 2.11266281 -0.70163806 16 -2.79657925 -1.17756299 17 -0.39618443 -1.60277178 18 -2.38109125 0.25505674 19 -0.84519632 0.39521130 20 0.46643806 0.04849672
Updated on: 06-Mar-2021
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