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Functional peace of mind

November 13, 2017
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I think what I enjoy the most about functional programming is the peace of mind that comes with it. With functional programming, there’s a lot of stuff you don’t need to think about. You can write functions that are general enough so that they solve a variety of problems. For example, imagine for a second that R does not...

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Easy peasy STATA-like marginal effects with R

Easy peasy STATA-like marginal effects with R

Model interpretation is essential in the social sciences. If one wants to know the effect of variable x on the dependent variable y, marginal effects are an easy way to get the answer. STATA includes a margins command that has been ported to R by Thomas J. Leeper of the London School of Economics and Political Science. You can...

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Why I find tidyeval useful

First thing’s first: maybe you shouldn’t care about tidyeval. Maybe you don’t need it. If you exclusively work interactively, I don’t think that learning about tidyeval is important. I can only speak for me, and explain to you why I personally ...

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Why I find tidyeval useful

First thing’s first: maybe you shouldn’t care about tidyeval. Maybe you don’t need it. If you exclusively work interactively, I don’t think that learning about tidyeval is important. I can only speak for me, and explain to you why I personally ...

Read more »

Why I find tidyeval useful

First thing’s first: maybe you shouldn’t care about tidyeval. Maybe you don’t need it. If you exclusively work interactively, I don’t think that learning about tidyeval is important. I can only speak for me, and explain to you why I personally ...

Read more »

tidyr::spread() and dplyr::rename_at() in action

I was recently confronted to a situation that required going from a long dataset to a wide dataset, but with a small twist: there were two datasets, which I had to merge into one. You might wonder what kinda crappy twist that is, right? Well, let’s take a look at the data: data1; data2 ## # A tibble: 20 x 4 ##...

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tidyr::spread() and dplyr::rename_at() in action

I was recently confronted to a situation that required going from a long dataset to a wide dataset, but with a small twist: there were two datasets, which I had to merge into one. You might wonder what kinda crappy twist that is, right? Well, let’s take a look at the data: data1; data2 ## # A tibble: 20 x 4 ##...

Read more »

tidyr::spread() and dplyr::rename_at() in action

I was recently confronted to a situation that required going from a long dataset to a wide dataset, but with a small twist: there were two datasets, which I had to merge into one. You might wonder what kinda crappy twist that is, right? Well, let’s t...

Read more »

Lesser known dplyr 0.7* tricks

This blog post is an update to an older one I wrote in March. In the post from March, dplyr was at version 0.50, but since then a major update introduced some changes that make some of the tips in that post obsolete. So here I revisit the blog post from March by using dplyr 0.70. Create new columns with...

Read more »

Lesser known dplyr 0.7* tricks

This blog post is an update to an older one I wrote in March. In the post from March, dplyr was at version 0.50, but since then a major update introduced some changes that make some of the tips in that post obsolete. So here I revisit the blog post from March by using dplyr 0.70. Create new columns with...

Read more »

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