Sept. 5, 2023, 11:04 a.m. | /u/takenorinvalid

Data Science

Every time I've tested a SQL query and realized that some null somewhere broke my CONCAT statement, or run an R script and realized that I forgot to add "na.rm = TRUE" to a function somewhere, I wonder what was going through the development team's minds when they decided to build these tools these ways.

Why isn't ignoring nulls the default behavior?

Genuinely curious if there's a logic to this that I haven't considered.

build datascience development function null query sql sql query team through true

Senior AI/ML Developer

@ | Remote

Consultant(e) Confirmé(e) Power BI & Azure - H/F

@ Talan | Lyon, France

Research Manager-Data Science

@ INFICON | East Syracuse, NY, United States

Data Scientist

@ Ubisoft | Singapore, Singapore

Data Science Assistant – Stage Janvier 2024 (F/H/NB)

@ Ubisoft | Paris, France

Data Scientist

@ dentsu international | Milano, Italy