Summary tables of large datasets including character and numerical variables
On 11-12-26 5:44 AM, sparandekar wrote:
Hello ! I am attempting to switch from being a long time SAS user to R, and would really appreciate a bit of help ! The first thing I do in getting a large dataset (thousands of obervations and hundreds of variables) is to run a SAS command PROC CONTENTS VARNUM command - this provides me a table with the name of each variable, its type and length; then I run a PROC MEANS - for numerical variables it gives me a table with the number of non-missing values, min, max, mean and std. dev. My data usually has errors and this first step helps me to spot the errors and 'clean' the dataset. The 'summary' function in R and other function as part of Hmisc or Psych package do not work for me. How can I get a table from an R data.frame that has the following structure (header row and example). Rowname Character/Integer Length Non-Missing Minimum Maximum Mean SD HHID Integer 12 32,344 114455007701 514756007812 2.345 x 10^10 1.456 x 10^10 Head Character 38 24,566 - - - -
Using the tables package, you can get something like that as follows, assuming that "df" is your dataframe: nonmissing <- function(x) sum(!is.na(x)) tabular(All(df, character=TRUE) ~ (typeof + length + nonmissing + min + max + mean + sd)) It isn't perfect: it will skip anything that isn't numeric or character (e.g. factors). There are ways to work around that, but they aren't as simple as you might like. You can also use sapply(df, class) to see the classes of all the columns. Duncan Murdoch