How we review code at Pew Research Center
As part of our quality control process, we review code with a series of interim reviews during a project and a formalized code check at the end.
A behind-the-scenes blog about research methods at Pew Research Center.
For our latest findings, visit pewresearch.org.
As part of our quality control process, we review code with a series of interim reviews during a project and a formalized code check at the end.
Building informative and digestible data visualizations is a foundational aspect of Pew Research Center’s work.
Our data science work typically involves multiple researchers working collaboratively on code.
We’re excited to release a collection of Python tools that we’ve found ourselves returning to again and again.
Three widely cited coronavirus trackers differ in their methods and in the kinds of information they provide.
Data from Pew Research Center’s annual Global Attitudes Survey is publicly available.
This post walks through the process of weighting and analyzing a survey dataset.
This post provides tips on recoding and collapsing survey data and displaying weighted estimates of categorical variables.
Our new R package contains various functions that we use in our day-to-day survey work.
Identifying causal relationships from observational data is not easy. Still, researchers are often interested in examining the effects of policy changes.