mikekaminsky

SELECT
    col_a
  , col_b
  , col_c
FROM table_a
LEFT JOIN table_b
  ON table_a.id = table_b.a_id

mikekaminsky

library(dplyr)
library(progress)
library(foreach)
library(doParallel)
library(tidyr)
library(magrittr)

##########################
# Blog Post Example
##########################

mikekaminsky

CREATE OR REPLACE FUNCTION kaplan_meier(text)
RETURNS TABLE (
  time_period int,
  pivot text,
  exposed int,
  events int,
  marginal_probability double precision,
  cumulative_probability double precision
) AS 
$PROC$

mikekaminsky

Testing for Analytics and Datascience

Introduction

Historically software development for research and for the sciences has not been well tested. This has been the case for a variety of reasons, including:

• Scientists and researchers are not developers, and simply don't know about best practices
• Non-deterministic functions are difficult to test
• Set-returning functions (most of data munging) are very time-consuming to test because you must generate a lot of test data
• It's really difficult to think through all of the possible edge cases like you might try in TDD