I have the daily data of two stocks (Apple and Google)
library(tidyquant)
dt = tidyquant::tq_get(c("AAPL", "GOOG")) %>%
arrange(symbol, date)
I am trying to convert this data from daily to weekly using the following code
result = dt %>%
group_by(symbol) %>%
tidyquant::tq_transmute(mutate_fun = to.weekly) %>% data.table
result[symbol == "AAPL" & date == "2017-02-03"]
Somehow, the result is wrong.
As an example, the weekly data for AAPL
on 2017-02-03
is coming as follows using the above code-
symbol date open high low close volume
1: AAPL 2017-02-03 32.0775 32.2975 32.04 32.27 98029200
However, the correct result should be -
symbol date open high low close volume
1: AAPL 2017-02-03 30.2325 32.6225 30.1550 32.2700 999124986
Can someone help me here?
Thanks!
At the time of writing: a bug, see github issue 148.
A possible workaround, using tidyr and timetk and purrr. Using timetk to get the data into xts format, transform data into weekly and turn back into a data.frame format. Including nest
and unnest
from tidyr and map
from purrr. data.table is not needed but prints the data a lot better than tibbles.
library(tidyr)
library(timetk)
# library(purrr)
result <- dt %>%
group_by(symbol) %>%
nest() %>%
mutate(data = purrr::map(data, function(x) x %>%
select(date, Open = open, High = high, Low = low, Close = close) %>%
tk_xts(x, select = c(Open, High, Low, Close), date_var = date) %>%
to.weekly %>%
tk_tbl)) %>%
unnest(data) %>%
rename_with( ~ tolower(gsub("..", "", .x, fixed = T))) %>%
rename(date = index)
result %>%
data.table %>%
filter(date == "2017-02-03")
symbol date open high low close
1: AAPL 2017-02-03 30.2325 32.6225 30.155 32.27
2: GOOG 2017-02-03 814.6600 815.8400 790.520 801.49