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January 21, 2021
Last year, pins got released as a brand new R package to pin, discover and cache remote resources for R users.
There's a point in every data wranglers' career in which their full dataset can no longer fit into just CSV files, and the journey to database-world begins.
While there has been a lot of excitement about the R and Python love story, there are still misconceptions that individuals, teams, or organizations must pick between R or Python.
Last January I left my job to spend a year developing siuba, a python port of dplyr. At its core, this decision was driven by a decade of watching python and R users produce similar analyses, but in very different ways.