minor typo (#1371)
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@ -448,7 +448,7 @@ knitr::include_graphics("diagrams/tidy-data/names-and-values.png", dpi = 270)
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## Widening data
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## Widening data
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So far we've used `pivot_longer()` to solve the common class of problems where values have ended up in column names.
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So far we've used `pivot_longer()` to solve the common class of problems where values have ended up in column names.
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Next we'll pivot (HA HA) to `pivot_wider()`, which which makes datasets **wider** by increasing columns and reducing rows and helps when one observation is spread across multiple rows.
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Next we'll pivot (HA HA) to `pivot_wider()`, which makes datasets **wider** by increasing columns and reducing rows and helps when one observation is spread across multiple rows.
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This seems to arise less commonly in the wild, but it does seem to crop up a lot when dealing with governmental data.
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This seems to arise less commonly in the wild, but it does seem to crop up a lot when dealing with governmental data.
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We'll start by looking at `cms_patient_experience`, a dataset from the Centers of Medicare and Medicaid services that collects data about patient experiences:
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We'll start by looking at `cms_patient_experience`, a dataset from the Centers of Medicare and Medicaid services that collects data about patient experiences:
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