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@ -67,7 +67,7 @@ I often add a comment (the line starting with `#`), to make it really clear wher
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## Tibbles vs. data frames
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There are two main differences in the usage of a data frame vs a tibble: printing, and subsetting.
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There are two main differences in the usage of a data frame vs a tibble: printing and subsetting.
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### Printing
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)
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```
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Tibbles are designed so that you don't accidentally overwhelm your console when you print large dataframes. But sometimes you need more output than the default display. There are a few options that can help.
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Tibbles are designed so that you don't accidentally overwhelm your console when you print large data frames. But sometimes you need more output than the default display. There are a few options that can help.
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First, you can explicitly `print()` the data frame and control the number of rows (`n`) and the `width` of the display. `width = Inf` will display all columns:
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### Subsetting
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So far all the tools you've learned have worked with complete dataframes. If you want to pull out a single variable, you need some new tools, `$` and `[[`. `[[` can extract by name or position; `$` only extracts by name but is a little less typing.
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So far all the tools you've learned have worked with complete data frames. If you want to pull out a single variable, you need some new tools, `$` and `[[`. `[[` can extract by name or position; `$` only extracts by name but is a little less typing.
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```{r}
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df <- tibble(
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