Problems with dplyr and POSIXlt data

Question

I have a problem. I downloaded data and tranformed dates into POSIXlt format

df<-read.csv("007.csv", header=T, sep=";")
df$transaction_date<-strptime(df$transaction_date, "%d.%m.%Y")
df$install_date<-strptime(df$install_date, "%d.%m.%Y")
df$days<- as.numeric(difftime(df$transaction_date,df$install_date, units = "days"))

Data frame is about transaction in one online game. It contains value (its payment), transaction_date, intall_date and ID. I added new column, which showndays after installation. I tried to summarise data using dlyr

df2<-df %>% group_by(days) %>% summarise(sum=sum(value))

And I've got an error: Error: column 'transaction_date' has unsupported type : POSIXlt, POSIXt

How can i Fix it?

UPD. I changed classes of Date columns into Character. It solved problem. But can i use dlyr withouts changing classes in my dataset?

Answer 1

You could use as.POSIXct as recommended in the comments but if the hours, minutes, and seconds don't matter then you should just use as.Date

df <- read.csv("007.csv", header=T, sep=";")

df2 <- df %>%
  mutate(
     transaction_date = as.Date(transaction_date, "%d.%m.%Y")
     ,install_date = as.Date(install_date, "%d.%m.%Y")
  ) %>%
  group_by(days = transaction_date - install_date) %>%
  summarise(sum=sum(value))

Answer 2

As noted here, this is a "feature" of the tidyverse. They don't want to handle POSIXlt object because it is some kind of list within a vector. However, using as.POSIXct isn't always an option. In my case I really needed the POSIXlt class to handle some uncleaned data. In that case, just go back to good old stable base R. In your case:

df2 <- aggregate(df1$value, by=list(df$days), sum)

Answer 3

One trick I use often is the following:

1. Convert POSIXt columns (in example below eventDate) to character
2. Perform dplyr operations you need (in example below we bind rows of two data frames)
3. Convert back from character to POSIXt not forgetting to set the right format (format) and timezone (tz) as it was before performing step 1.

Example:

# step 1
df1$eventDate <- as.character.POSIXt(df1$eventDate)
df2$eventDate <- as.character.POSIXt(df2$eventDate)
#step 2
merged_df <- bind_rows(df1, df2)
#step 3
merged_df$eventDate <- strptime(merged_df$eventDate, format = "%Y-%m-%d", tz = "UTC")