Function over multiple dataframes in R

Question

I have a set of survey design data for each quarter/year in RDs format on my disk. The data is like this:

Year  Quarter  Age
2010     1     27
2010     1     32 
2010     1     34
...

I'm using the function svymean(formula=~Age, na.rm = T, design = data20101) to estimate the mean of the age variable for each year/quarter file. I would like to run this more efficiently in a way that I could run the function and then save the results in one single data frame.

The output I'm looking for is to produce such a dataframe:

Year  Quarter  Mean_Age
2010     1       31.1
2010     1       32.4 
2010     1       30.9
2010     1       34.5
2010     2       36.3
2010     2       31.2
2010     2       30.8
2010     2       35.6
...

Regards,

bdedu · Accepted Answer · 2021-11-13 16:31:15Z

1

lapply and package dplyr should do the work. Here is an example.

library(dplyr)

df1 <- data.frame(cbind("Year" = rep(2010, 6),
                        "Quarter" = c(1, 1, 1, 2, 2, 2),
                        "Age" = c(27, 32, 34, 30, 28, 21))
)

df2 <- data.frame(cbind("Year" = rep(2010, 6),
                        "Quarter" = c(1, 1, 1, 2, 2, 2),
                        "Age" = c(23, 19, 31, 41, 26, 23))
)

df.list <- list(df1, df2)

mean.list <- lapply(df.list, function(x){
  x %>%
    group_by(Year, Quarter) %>%
    summarize(Mean_Age = mean(Age, na.rm = TRUE))
})

mean.df <- do.call(rbind, mean.list)

mean.df

The result will be

# A tibble: 4 x 3
# Groups:   Year [1]
   Year Quarter Mean_Age
  <dbl>   <dbl>    <dbl>
1  2010       1     31  
2  2010       2     26.3
3  2010       1     24.3
4  2010       2     30

answered Nov 13, 2021 at 16:31

bdedu

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