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Tweak cheatsheet images
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README.Rmd

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str_sub(x, 1, 2)
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```
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See a complete list on the cheatsheet:
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<a href="https://github.com/rstudio/cheatsheets/blob/master/strings.pdf"><img src="man/figures/cheatsheet-thumb.png" width="300" height="232"/></a>
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Most string functions work with regular expressions, a concise language for describing patterns of text. For example, the regular expression `"[aeiou]"` matches any single character that is a vowel:
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```{r}
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* `boundary()`: match boundaries
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<a href="https://github.com/rstudio/cheatsheets/blob/master/strings.pdf"><img src="man/figures/cheatsheet-thumb.png" align="right" dpi="600"/></a>
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## Compared to base R
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R provides a solid set of string operations, but because they have grown organically over time, they can be inconsistent and a little hard to learn. Additionally, they lag behind the string operations in other programming languages, so that some things that are easy to do in languages like Ruby or Python are rather hard to do in R.

README.md

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#> [1] "wh" "vi" "cr" "ex" "de" "au"
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```
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See a complete list on the
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cheatsheet:
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<a href="https://github.com/rstudio/cheatsheets/blob/master/strings.pdf"><img src="man/figures/cheatsheet-thumb.png" width="300" height="232"/></a>
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Most string functions work with regular expressions, a concise language
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for describing patterns of text. For example, the regular expression
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`"[aeiou]"` matches any single character that is a vowel:
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- `fixed()`: match exact bytes
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- `coll()`: match human letters
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- `boundary()`: match
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boundaries
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<a href="https://github.com/rstudio/cheatsheets/blob/master/strings.pdf"><img src="man/figures/cheatsheet-thumb.png" align="right" dpi="600"/></a>
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- `boundary()`: match boundaries
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## Compared to base R
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man/figures/cheatsheet-thumb.png

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man/figures/[email protected]

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