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.
Coding How-To
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What we learned from creating a custom graphics package in R using ggplot2
Building informative and digestible data visualizations is a foundational aspect of Pew Research Center’s work.
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How Pew Research Center uses git and GitHub for version control
Our data science work typically involves multiple researchers working collaboratively on code.
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Introducing Pew Research Center’s Python libraries
We’re excited to release a collection of Python tools that we’ve found ourselves returning to again and again.
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The challenges of using real-time epidemiological data in a public health crisis
Three widely cited coronavirus trackers differ in their methods and in the kinds of information they provide.
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Analyzing international survey data with the pewmethods R package
Data from Pew Research Center’s annual Global Attitudes Survey is publicly available.
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Weighting survey data with the pewmethods R package
This post walks through the process of weighting and analyzing a survey dataset.
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Exploring survey data with the pewmethods R package
This post provides tips on recoding and collapsing survey data and displaying weighted estimates of categorical variables.
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Introducing pewmethods: An R package for working with survey data
Our new R package contains various functions that we use in our day-to-day survey work.
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Using fixed and random effects models for panel data in Python
Identifying causal relationships from observational data is not easy. Still, researchers are often interested in examining the effects of policy changes.
About Decoded
This is a blog about research methods and behind-the-scenes technical matters at Pew Research Center. To get our latest findings, visit pewresearch.org.
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