Summarizing count and conditional aggregate functions on the same factor

Question

Quick and short of it is I\'m having problems summarizing count and aggregate functions with conditions on the same factor.

Suppose I have this dataframe:

Answer 1

Assuming that your original dataset is similar to the one you created (i.e. with NA as character. You could specify na.strings while reading the data using read.table. But, I guess NAs would be detected automatically.

The price column is factor which needs to be converted to numeric class. When you use as.numeric, all the non-numeric elements (i.e. "NA", FALSE) gets coerced to NA) with a warning.

library(dplyr)
df %>%
     mutate(price=as.numeric(as.character(price))) %>%  
     group_by(company, year, product) %>%
     summarise(total.count=n(), 
               count=sum(is.na(price)), 
               avg.price=mean(price,na.rm=TRUE),
               max.price=max(price, na.rm=TRUE))

data

I am using the same dataset (except the ... row) that was showed.

df = tbl_df(data.frame(company=c("Acme", "Meca", "Emca", "Acme", "Meca","Emca"),
 year=c("2011", "2010", "2009", "2011", "2010", "2013"), product=c("Wrench", "Hammer",
 "Sonic Screwdriver", "Fairy Dust", "Kindness", "Helping Hand"), price=c("5.67",
 "7.12", "12.99", "10.99", "NA",FALSE)))