Data Manipulation in Clojure Compared to R and Python

Published 2024-07-18

I spend a lot of time developing and teaching people about Clojure's open source tools for working with data. Almost everybody who wants to use Clojure for this kind of work is coming from another language ecosystem, usually R or Python. Together with Daniel Slutsky, I'm working on formalizing some of the common teachings into a course. Part of that is providing context for people coming from other ecosystems, including "translations" of how to accomplish data science tasks in Clojure.

As part of this development, I wanted to share an early preview in this blog post. The format is inspired by this great blog post I read a while ago comparing R and Polars side by side (where "R" here refers to the tidyverse, an opinionated collection of R libraries for data science, and realistically mostly dplyr specifically). I'm adding Pandas because it's among the most popular dataset manipulation libraries, and of course Clojure, specifically tablecloth, the primary data manipulation library in our ecosystem.

I'll use the same dataset as the original blog post, the Palmer Penguin dataset. For the sake of simplicity, I saved a copy of the dataset as a CSV file and made it available on this website. I will also refer the data as a "dataset" throughout this post because that's what Clojure people call a tabular, column-major data structure, but it's the same thing that is variously referred to as a dataframe, data table, or just "data" in other languages. I'm also assuming you know how to install the packages required in the given ecosystems, but any necessary imports or requirements are included in the code snippets the first time they appear. Versions of all languages and libraries used in this post are listed at the end. Here we go!

Reading data

Reading data is straightforward in every language, but as a bonus we want to be able to indicate on the fly which values should be interpreted as "missing", whatever that means in the given libraries. In this dataset, the string "NA" means "missing", so we want to tell the dataset constructor this as soon as possible. Here's the comparison of how to accomplish that in various languages:

Tablecloth

(require '[tablecloth.api :as tc]) (def ds (tc/dataset "https://codewithkira.com/assets/penguins.csv"))

Note that tablecloth interprets the string "NA" as missing ( nil , in Clojure) by default.

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