purrr is a package that extends R’s functional programming capabilities. It brings a lot of new stuff to the table and in this post I show you some of the most useful (at least to me) functions included in purrr. Getting rid of loops with map()

library(purrr)

numbers <- list(11, 12, 13, 14)

map_dbl(numbers, sqrt)

## [1] 3.316625 3.464102 3.605551 3.741657

You ... [Read more...]

In this blog post I share some lesser-known (at least I believe they are) tricks that use mainly functions from dplyr. Removing unneeded columns Did you know that you can use - in front of a column name to remove it from a data frame?

mtcars %>% 
    select(-disp) %>% 
    head()

##                    mpg cyl  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6 105 2.76 3.460 20.22  1  0    3    1

Re-ordering columns Still ... [Read more...]

In this blog post I share some lesser-known (at least I believe they are) tricks that use mainly functions from dplyr. Removing unneeded columns Did you know that you can use - in front of a column name to remove it from a data frame?

mtcars %>% 
    select(-disp) %>% 
    head()

##                    mpg cyl  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6 105 2.76 3.460 20.22  1  0    3    1

Re-ordering columns Still ... [Read more...]

What is jailbreakr The jailbreakr package is probably one of the most interesting packages I came across recently. This package makes it possible to extract messy data from spreadsheets. What is meant by messy? I am sure you already had to deal with spreadsheets that contained little tables inside a ... [Read more...]

What is jailbreakr The jailbreakr package is probably one of the most interesting packages I came across recently. This package makes it possible to extract messy data from spreadsheets. What is meant by messy? I am sure you already had to deal with spreadsheets that contained little tables inside a ... [Read more...]

I’m currently writing a book as a hobby. It’s titled Functional programming and unit testing for data munging with R and you can get it for free here. You can also read it online for free on my webpage What’s the book about? Here’s the teaser ... [Read more...]

The book I’ve been working on these pasts months (you can read about it here, and read it for free here) is now available on Leanpub! You can grab a copy and read it on your ebook reader or on your computer, and what’s even better is that ... [Read more...]

Analyzing a lot of datasets can be tedious. In my work, I often have to compute descriptive statistics, or plot some graphs for some variables for a lot of datasets. The variables in question have the same name accross the datasets but are measured for different years. As an example, ... [Read more...]

I have started writing a ‘book’ using the awesome bookdown package. In the book I explain and show why using functional programming and putting your functions in your own packages is the way to go when you want to clean, prepare and transform large data sets. It makes testing and ... [Read more...]

Last week I showed how to read a lot of datasets at once with R, and this week I’ll continue from there and show a very simple function that uses this list of read datasets and merges them all together. First we’ll use read_list() to read all ... [Read more...]

I often have to read a lot of datasets at once using R. So I’ve wrote the following function to solve this issue:

read_list <- function(list_of_datasets, read_func){

        read_and_assign <- function(dataset, read_func){
                dataset_name <- as.name(dataset)
                dataset_name <- read_func(dataset)
        }

        # invisible is used to suppress the unneeded output
        output <- invisible(
                sapply(list_of_datasets,
                           read_and_assign, read_func = read_func, simplify = FALSE, USE.NAMES = TRUE))

        # Remove the extension at the end of the data set names
        names_of_datasets <- c(unlist(strsplit(list_of_datasets, "[.]"))[c(T, F)])
        names(output) <- names_of_datasets
        return(output)
}

You need to supply a list of datasets as well as the function to read the datasets to read_list. So for example to read ... [Read more...]

Suppose that you would like to create a function which does a series of computations on a data frame. You would like to pass a column as this function’s argument. Something like:

data(cars)
convertToKmh <- function(dataset, col_name){
  dataset$col_name <- dataset$speed * 1.609344
  return(dataset)
}

This example is obviously not very interesting (you don’t need a function for this), but ... [Read more...]

tryCatch is one of the functions that allows the users to handle errors in a simple way. With it, you can do things like: if(error), then(do this). Take the following example:

sqrt("a")
Error in sqrt("a") : non-numeric argument to mathematical function

Now maybe you’d want something to happen when such an error happens. You can achieve ... [Read more...]

I've been introduced to unit testing while working with colleagues on quite a big project for which we use Python. At first I was a bit skeptical about the need of writing unit tests, but now I must admit that I am seduced by the idea and by the huge ... [Read more...]

I’m currently working on a paper (with my colleague Vincent Vergnat who is also a Phd candidate at BETA) where I want to estimate the causal impact of the birth of a child on hourly and daily wages as well as yearly worked hours. For this we are using ... [Read more...]