Iteration is a powerful way to make the computer do the work for you. It can also be an area of coding where it is easy to make lots of typos and simple mistakes. The purrr package helps simplify iteration so you can focus on the next step, instead of finding typos.

The power of iteration

Introduction to iteration

Iteration with purrr

More iteration with for loops

More iteration with purrr

Subsetting lists

List structure

Subsetting list elements

The many flavors of map()

map() argument alternatives

map_*

Simplifying Iteration and Lists With purrr

purrr is much more than a for loop; it works well with pipes, we can use it to run models and simulate data, and make nested loops!

Lavorare con liste senza nome

Ripasso su nomi e pipe

Impostare i nomi

Pipe in map()

Altre funzioni di map()

Simulare dati con purrr

Esegui un modello lineare

map_chr()

map_dbl() e map_int()

map2() e pmap()

Simulare dati con input multipli usando map2()

Simulare dati con 3+ input usando pmap()

More complex iterations

Like anything in R, understanding how to troubleshoot issues is an important skill set. This can be particularly important with lists, where finding the problem can be tricky.

How to purrr safely()

safely() replace with NA

Convert data to numeric with purrr

Finding the problem areas

Another way to possibly() purrr

Replace safely() with possibly()

Convert values with possibly()

purrr is a walk() in the park

Comparing walk() vs. no walk() outputs

walk() for printing cleaner list outputs

Troubleshooting lists with purrr

Now that you have the building blocks, we will start tackling some more complex data problems with purrr.

Using purrr in your workflow

Name review

Setting names

Asking questions from a list

Even more complex problems

Questions about gh_repos

Graphs in purrr

ggplot() refresher

purrr and scatterplots

purrr and histograms

Wrap Up

Problem solving with purrr

Simulated data 1990-2005

Le liste possono essere difficili sia da capire sia da manipolare, ma racchiudono tantissime informazioni e sono molto potenti. In questo corso imparerai a estrarre, riassumere e manipolare facilmente le liste e a esportare i dati nell’oggetto che preferisci, che sia un’altra lista, un vettore o altro ancora! Durante il corso lavorerai con il pacchetto purrr e con vari insiemi di dati del pacchetto repurrrsive, inclusi dati da Star Wars e dai film di Wes Anderson, oltre a dati raccolti su utenti e repository GitHub. Alla fine del corso, le tue abilità con le liste saranno purrrfette!

Introduction to the Tidyverse

Intermediate R

Impara a usare il pacchetto purrr e i dataset di repurrrsive per gestire e risolvere liste.

Lavorare con liste senza nome

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