Add value to a dataframe without using forloop in-CodePudding

I am writing R, and I want to add a new column WITHOUT using for loop.

Here's the thing I want to do:

I want to calculate the mean from the first value to the current value.

If I use for loop, I will do in this way:

for (i in c(1:nrow(data))){
   data$Xn_bar[i] = mean(data$Xn[1:i])
}

Is there other way(i.e. map?)

Here's the data:

a = data.frame(
  n = c(1:10),
  Xn = c(-0.502,0.132,-0.079,0.887,0.117,0.319,-0.582,0.715,-0.825,-0.360)
)

CodePudding user response：

You can do this with dplyr::cummean() or calculate it in base R by dividing the cumulative sum by the number of values so far:

cumsum(a$Xn) / seq_along(a$Xn) # base R

dplyr::cummean(a$Xn) # dplyr

# Output in both cases
#  [1] -0.50200000 -0.18500000 -0.14966667  0.10950000  0.11100000  0.14566667  0.04171429
#  [8]  0.12587500  0.02022222 -0.01780000

CodePudding user response：

Here is one solution using row_number() of dplyr and mapply() function:

library(dplyr)
df=data.frame(n=c(1,2,3,4,5),
             Xn=c(-0.502,0.132,-0.079,0.887,0.117))

# add column row_index which contain row_number of current row 
df= df%>%
  mutate(row_index=row_number())

# Add column Xxn 
df$Xxn=mapply(function(x,y)return(
  round(
    mean(
      df$Xn[1:y]),3
    )
  ),
          df$Xn,
          df$row_index,
          USE.NAMES = F)
  
  #now remove  row_index column
df= df%>%select(-row_index)
df
# > df
# n     Xn    Xxn
# 1 1 -0.502 -0.502
# 2 2  0.132 -0.185
# 3 3 -0.079 -0.150
# 4 4  0.887  0.110
# 5 5  0.117  0.111