Reputation: 680
I have a datframe with that I want to calculate the percent change day by day and also over three days but when I do it the results don't really seem right.
ads <- data.frame(ad = c(ad1, ad1, ad1, ad1, ad2, ad2, ad2, ad3, ad3, ad3),
date = c("11-10", "11-11", "11-12", "11-13", "11-10", "11-11", "11-12", "11-10", "11-11", "11-12"),
likes = c(20, 30, 18, 5, 34, 68, 55, 44, 33, 20),
comments = c(21, 22, 10, 1, 10, 43, 24, 34, 21, 11))
so for I have this:
daily_pct <- function(x) x/lag(x)
three_pct <- function(x) x/lag(x ,k = 3)
daily_pct_change <- ads %>%
mutate_each(funs(daily_pct), c(likes,comments))
three_pct_change <- ads %>%
mutate_each(funs(three_pct), c(likes, comments))
Am I doing this correctly? I can't figure out how to get the three day one to work either. Thanks!
Upvotes: 0
Views: 585
Reputation: 39858
You can try:
df %>%
mutate_at(.vars = vars(dplyr::matches("(likes)|(comments)")),
funs(daily_change = ./lag(.)*100,
three_day_change = ./lag(., 3)*100))
Similarly, if you do not need the ad and date variables:
df %>%
select(likes, comments) %>%
mutate_all(funs(daily_change = ./lag(.)*100,
three_day_change = ./lag(., 3)*100))
Or if you need them:
df %>%
select(likes, comments) %>%
mutate_all(funs(daily_change = ./lag(.)*100,
three_day_change = ./lag(., 3)*100)) %>%
rowid_to_column() %>%
left_join(df %>% rowid_to_column() %>% select(rowid, ad, date), by = c("rowid" = "rowid")) %>%
select(-rowid)
Also, you can get the same results by a small modification of your original code:
daily_pct <- function(x) x/lag(x)*100
three_pct <- function(x) x/lag(x, 3)*100
df %>%
mutate_at(.vars = vars(dplyr::matches("(likes)|(comments)")),
funs(daily_change = daily_pct,
three_day_change = three_pct))
Upvotes: 1