CODEWITHSUNDEEP
rdata.table
ANmike
ANmike

Reputation: 267

Calculating average Based on Condition in R

Referring to the question "Calculating average of based on condition", I need to calculate average of the column E based on the column F

Below is my part of data frame df but my actual data is 65K values. 

        E            F        
     3.130658445    -1
     4.175605237    -1
     4.949554963    0
     4.653496112    0
     4.382672845    0
     3.870951272    0
     3.905365677    0
     3.795199341    0
     3.374740696    0
     3.104690415    0
     2.801178871    0
     2.487881321    0
     2.449349554    0
     2.405409636    0
     2.090901539    0
     1.632416356    0
     1.700583696    0
     1.846504012    0
     1.949797831    0
     1.963114449    0
     2.033100326    0
     2.014312751    0
     1.997178247    0
     2.143775497    0

Based on the solution provided in the mentioned post, below is my script. 

setDT(df)[, Avg := c(rep(mean(head(d$fE, 5)), 5), rep(0, .N-5)), 
      cumsum(c(TRUE,  diff(abs(F)!=1)==1))]

But when executed I am getting the below error.

Error in rep(0, .N - 5) : invalid 'times' argument

Upvotes: 2

Views: 6302

Answers (2)

Orhan Yazar
Orhan Yazar

Reputation: 909

Try this : dt<-data.table(df) dt[,Avg:=mean(E),by="F"] dt <- unique(dt,by="F")

this is the result:

 `E  F      Avg
1: 3.130658 -1 3.653132
2: 4.949555  0 2.797826

Doing only this : dt<-data.table(df) dt[,Avg:=mean(E),by="F"]

You get: E F Avg 1: 3.130658 -1 3.653132 2: 4.175605 -1 3.653132 3: 4.949555 0 2.797826 4: 4.653496 0 2.797826 5: 4.382673 0 2.797826 6: 3.870951 0 2.797826 7: 3.905366 0 2.797826 8: 3.795199 0 2.797826 9: 3.374741 0 2.797826 10: 3.104690 0 2.797826 11: 2.801179 0 2.797826 12: 2.487881 0 2.797826 13: 2.449350 0 2.797826 14: 2.405410 0 2.797826 15: 2.090902 0 2.797826 16: 1.632416 0 2.797826 17: 1.700584 0 2.797826 18: 1.846504 0 2.797826 19: 1.949798 0 2.797826 20: 1.963114 0 2.797826 21: 2.033100 0 2.797826 22: 2.014313 0 2.797826 23: 1.997178 0 2.797826 24: 2.143775 0 2.797826

Upvotes: 0

Sam
Sam

Reputation: 1482

use aggregate:

agg <- aggregate(df$E,by=list(df$F), FUN=mean)

you used a data table example, but you said data frame in your qu data table:

# this will retain all rows and return mean as a new column (per group_
df[, Mean:=mean(E), by=list(F)]
# this will return means per group only
df[, mean(E),by=.(F)]

Upvotes: 1

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