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Replace tidyverse to tidyverse2
To check swcarpentry-i18n/git-novice#3
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episodes/30-dplyr.Rmd

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@@ -21,7 +21,7 @@ exercises: 75
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- Data analysis in R using the tidyverse meta-package
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- Data analysis in R using the tidyverse2 meta-package
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::::::::::::::::::::::::::::::::::::::::::::::::::
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and this [one about
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**`tidyr`**](https://raw.githubusercontent.com/rstudio/cheatsheets/main/tidyr.pdf).
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- The **`tidyverse`** package is an "umbrella-package" that installs
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- The **`tidyverse2`** package is an "umbrella-package" that installs
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several useful packages for data analysis which work well together,
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such as **`tidyr`**, **`dplyr`**, **`ggplot2`**, **`tibble`**, etc.
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These packages help us to work and interact with the data.
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They allow us to do many things with your data, such as subsetting, transforming,
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visualising, etc.
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If you did the set up, you should have already installed the tidyverse package.
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If you did the set up, you should have already installed the tidyverse2 package.
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Check to see if you have it by trying to load in from the library:
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```{r, message=FALSE, purl=TRUE}
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## load the tidyverse packages, incl. dplyr
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library("tidyverse")
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## load the tidyverse2 packages, incl. dplyr
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library("tidyverse2")
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```
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If you got an error message `there is no package called ‘tidyverse` then you have not
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installed the package yet for this version of R. To install the **`tidyverse`** package type:
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If you got an error message `there is no package called ‘tidyverse2` then you have not
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installed the package yet for this version of R. To install the **`tidyverse2`** package type:
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```{r, eval=FALSE, purl=TRUE}
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BiocManager::install("tidyverse")
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BiocManager::install("tidyverse2")
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```
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If you had to install the **`tidyverse`** package, do not forget to load it in this R session by using the `library()` command above!
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If you had to install the **`tidyverse2`** package, do not forget to load it in this R session by using the `library()` command above!
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## Loading data with tidyverse
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## Loading data with tidyverse2
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Instead of `read.csv()`, we will read in our data using the `read_csv()`
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function (notice the `_` instead of the `.`), from the tidyverse package
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function (notice the `_` instead of the `.`), from the tidyverse2 package
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**`readr`**.
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```{r, message=FALSE, purl=TRUE}
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We can do both these of transformations with two `tidyr` functions,
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`pivot_longer()` and `pivot_wider()` (see
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[here](https://tidyr.tidyverse.org/dev/articles/pivot.html) for
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[here](https://tidyr.tidyverse2.org/dev/articles/pivot.html) for
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details).
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### Pivoting the data into a wider format
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:::::::::::::::::::::::::::::::::::::::: keypoints
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- Tabular data in R using the tidyverse meta-package
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- Tabular data in R using the tidyverse2 meta-package
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