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Fix typo (#256)

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harrismcgehee 2016-08-15 08:33:25 -04:00 committed by Hadley Wickham
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@ -8,7 +8,7 @@
> "Tidy datasets are all alike, but every messy dataset is messy in its
> own way." --– Hadley Wickham
In this chapter, you will learn a consistent way to organise your data in R, a organisation called __tidy data__. Getting your data into this format requires some upfront work, but that work pays off in the long-term. Once you have tidy data and the tidy tools provided by packages in the tidyverse, you will spend much less time munging data from one representation to another, allowing you to spend more time on the analytic questions at hand.
In this chapter, you will learn a consistent way to organise your data in R, an organisation called __tidy data__. Getting your data into this format requires some upfront work, but that work pays off in the long-term. Once you have tidy data and the tidy tools provided by packages in the tidyverse, you will spend much less time munging data from one representation to another, allowing you to spend more time on the analytic questions at hand.
This chapter will give you a practical introduction to tidy data and the accompanying tools in the __tidyr__ package. If you'd like to learn more about the underlying theory, you might enjoy the *Tidy Data* paper published in the Journal of Statistical Software, <http://www.jstatsoft.org/v59/i10/paper>.