1. Learn
    2. /
  2. Courses
    3. /
  3. Intermediate Functional Programming with purrr
  • 1

    Programming with purrr

    Free

    Do lambda functions, mappers, and predicates sound scary to you? Fear no more! After refreshing your purrr memory, we will dive into functional programming 101, discover anonymous functions and predicates, and see how we can use them to clean and explore data.

  • 2

    Functional programming: from theory to practice

    Ready to go deeper with functional programming and purrr? In this chapter, we'll discover the concept of functional programming, explore error handling using including safely() and possibly(), and introduce the function compact() for cleaning your code.

  • 3

    Better code with purrr

    In this chapter, we'll use purrr to write code that is clearer, cleaner, and easier to maintain. We'll learn how to write clean functions with compose() and negate(). We'll also use partial() to compose functions by "prefilling" arguments from existing functions. Lastly, we'll introduce list-columns, which are a convenient data structure that helps us write clean code using the Tidyverse.

  • 4

    Case study

    We'll wrap up everything we know about purrr in a case study. Here, we'll use purrr to analyze data that has been scraped from Twitter. We'll use clean code to organize the data and then we'll identify Twitter influencers from the 2018 RStudio conference.

Initializing

Exercise

Split up with keep() and discard()

We want to split our results into two groups: the days over 100, and the days under 100. We'll combine keep() and discard() to do so.

Why two functions? Couldn't we use one function? Couldn't we create a mapper called is_less_than_hundred?

We could, but that would be more error-prone: it's easier to switch from keep() to discard() than copying and pasting. By combining both functions, we only need one mapper. That means that if we want to change the threshold, we'll only need to do it once, not twice, as we would have to do if we had two mappers.

This is a rule you should endeavor to apply when coding: write code so that if you need to change one thing, you will have to change it just once.

all_visits is still available in your workspace.

Instructions

100 XP
  • Map the set_names() function on all_visits to add the name of the days: all_visits_named.
  • Create a mapper called threshold that will test if .x is over 100.
  • Create group_over by keeping the elements that are over 100.
  • Create group_under by discarding the elements that are over 100.