Get startedGet started for free

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

View Course

Exercise instructions

  • Use map() to compute over every nested data frame of data.
  • 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)
    )
  }))
Edit and Run Code