Using Stargazer in R to export csv direct into Excel -

i trying stargazer r package spit out huge .csv. descriptive statistics table 43 different companies excel.

i have 43 different data frames pertaining meetings @ 43 different corporation. trying create output each 1 of these data frames list mean value of variable of meetings, standard deviation of variable august, max, min, , total number. reproducible example below company 1 "j" standing july, "a" august, "s" september, , "n" november:

j      s   n 29  2   30   2 20  3   30  10 30  10  20  30 40  20  10  21 10  30  13  14 

company 2

j     s   n 14  5   15  19 10  10  17  10 30  14  18  11 10  20  19  9 10  10  20  4 

the following code used:

stargazer(company1[c("j", "a", "s", "n")], type = "text",        title="descriptive statistics company 1", digits=1, out="table1.txt",       covariate.labels= c("j", "a", "s", "n"))  stargazer(company2[c("j", "a", "s", "n")], type = "text",        title="descriptive statistics augustmartin", digits=1, out="table1.txt",       covariate.labels= c("j", "a", "s", "n"))  ... stargazer(company43[c("j", "a", "s", "n")], type = "text",        title="descriptive statistics augustmartin", digits=1, out="table1.txt",       covariate.labels= c("j", "a", "s", "n")) 

i trying stargazer package take descriptive statistics company 1 company 43, preserve headings know descriptive statistics belong company , dump them convenient csv sheet in excel.

when try use following code

library(xlsx) # create single summary table , write excel file tab1 = t(sapply(company1, function(x) { data.frame(n=length(x), mean=mean(x), `st. dev.`=sd(x), min=min(x),     max=max(x)) })) write.xlsx(tab1, "company data.xlsx", sheetname="company1", row.names=false) 

i following:

col 1   col2     col3    col4 51.34   #n/a    51.34   51.34 7.58    #n/a    7.58    7.58 26.99   #n/a    26.99   26.99 49.74   #n/a    49.74   49.74 34.84   #n/a    34.84   34.84 54.84   #n/a    54.84   54.84 18.5    #n/a    18.5    18.5   49.34   #n/a    49.34   49.34 49.26   #n/a    49.26   49.26 

it taking mean of each row , not mean of specified column. ideally add in col 1, find mean, standard deviation, min , max.

stargazer doesn't seem right tool this. instead, create data frame summary data want , write excel file. below provide examples single data frame , bunch of data frames.

save summary of single data frame

library(xlsx)  # create single summary table , write excel file tab1 = t(sapply(company1, function(x) {   data.frame(n=length(x), mean=mean(x), `st. dev.`=sd(x), min=min(x), max=max(x)) }))  write.xlsx(tab1, "company data.xlsx", sheetname="company1", row.names=false) 

save summaries of multiple data frames

here's how write bunch of summary tables file. ideally, read data frames list , operate on each element of list. way won't have repeat same code each individual data frame.

to create list of data frames, read in data this:

# names of files read file.names = list.files(pattern="company.*csv") df.list = sapply(file.names, read.csv) 

for example, i'll create list of data frames using sample data company1 , company2 provided:

df.list = list(company1=company1, company2=company2)  # calculate summary statistics each data frame , write excel worksheet sapply(names(df.list), function(df) {    tab1 = t(sapply(df.list[[df]], function(x) {     data.frame(n=length(x), mean=mean(x), `st. dev.`=sd(x), min=min(x), max=max(x))   }))    write.xlsx(tab1, "company data.xlsx", sheetname=df, row.names=false, append=true) })