Month: March 2019

Good use of R’s tapply function to summary data ..

## read a csv file into a table called x – the first row contains column names

x<-read.table("2014-tax.csv",sep=",",header=T)

## In my instance column names are Item,Amount,Cat,Month,Who
## split out by Who

bob<-x[x$Who == "bob",] jane<-x[x$Who == "jane",]

## Spin around each row (obs) and sum the Amount

print(tapplybob$Amount,bob$Cat,sum))

## Typical output for bob #

#  books  equipment licences stationery  supplies    telephone 
#  303.00  694.27     132.00   345.50      96.00       30.00 
#  

# Then for jane

print(tapply(jane$Amount,jane$Cat,sum)) 

# books equipment licences stationery supplies telephone 
# 163.0  583.0      348.0     678.4    11543.0    NA 
# 
#