CODEWITHSUNDEEP
rif-statement
oercim
oercim

Reputation: 1848

Complex multiple if statements

Let I have such a dataframe (df) 

ID    x1   x2   y    
1    1    0    0.21
2    1    0    0.56
3    1    1    0.34
4    0    1    0.76
5    1    1    0.06
6    1    0    0.45
7    0    1    0.56
8    0    1    0.83
9    0    1    0.64
10   0    0    0.44
11   1    0    0.54

I want to create a new colunm(z) in df which obey the below conditions:

{if(x1=1 and x2=0 and y<0.5)

then z=x2(namely 0)}

{if(x1=0 and x2=1 and y>0.5)

then z=x2(namely 1)}

else z=x1

Namely z must be outputed like below:

   ID  z
    1   0
    2   1
    3   1
    4   1
    5   1
    6   0
    7   1
    8   1
    9   1
    10  0
    11  1

How can I do this using R? ifelse statement seem to me so complex with these conditions.

Upvotes: 1

Views: 81

Answers (2)

IRTFM
IRTFM

Reputation: 263321

I dragged your conditions to my workspace and lightly editted them to make a Boolean calculation by replacing = with ==; and with &; and otherwise with the negation of the two conditions, . The conditionals are 0 when FALSE and 1 when TRUE so act as selectors. Could also have used nested ifelse functions, but I often find them messy. In this case Jilber proved me misguided (but not wrong.):

 dat$z <- with(dat,   (x1==1 & x2==0 & y<0.5)*x2+
                      (x1==0 & x2==1 & y>0.5)*x2+
                    (!(x1==1 & x2==0 & y<0.5) & !(x1==0 & x2==1 & y>0.5))*x1)

> dat
   ID x1 x2    y z
1   1  1  0 0.21 0
2   2  1  0 0.56 1
3   3  1  1 0.34 1
4   4  0  1 0.76 1
5   5  1  1 0.06 1
6   6  1  0 0.45 0
7   7  0  1 0.56 1
8   8  0  1 0.83 1
9   9  0  1 0.64 1
10 10  0  0 0.44 0
11 11  1  0 0.54 1

Upvotes: 3

Jilber Urbina
Jilber Urbina

Reputation: 61154

Use nested ifelse. Consider df is your dataframe, then:

> df$z <- with(df, ifelse(x1==1 & x2==0 & y<0.5, x2, 
                          ifelse(x1==0 & x2==1 & y>0.5, x2,x1 )))
> 
> df
   ID x1 x2    y z
1   1  1  0 0.21 0
2   2  1  0 0.56 1
3   3  1  1 0.34 1
4   4  0  1 0.76 1
5   5  1  1 0.06 1
6   6  1  0 0.45 0
7   7  0  1 0.56 1
8   8  0  1 0.83 1
9   9  0  1 0.64 1
10 10  0  0 0.44 0
11 11  1  0 0.54 1

Upvotes: 3

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