Cognostics from nested data frames
Let's compute the average close price, average volume, and annual return as cognostics. The variables that these are based on, open
, close
, and volume
, are inside the nested data frame data
in our by_symbol
dataset.
Note that a function, annual_return()
, has been provided for convenience.
This exercise is part of the course
Visualizing Big Data with Trelliscope in R
Exercise instructions
- Use
map()
to compute over every nested data frame ofdata
. - Inside the map function, create a summary data frame containing the average close price, the average volume, and the annual percentage return. Take a look at
by_symbol$data[[1]]
to recall the column names that are available.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
library(trelliscopejs)
library(dplyr)
library(purrr)
annual_return <- function(x)
100 * (tail(x$close, 1) - head(x$open, 1)) / head(x$open, 1)
# Compute by_symbol_avg
by_symbol_avg <- mutate(by_symbol,
stats = ___(___, function(x) {
data_frame(
mean_close = mean(x$___),
mean_volume = mean(x$___),
annual_return = annual_return(x)
)
}))