05-Q_and_A.Rmd

# Questions and Answers {#questions-and-answers}

A list of questions that may arise during the use of R and their answers. When you have questions that remain unanswered, feel free to reach out!

### What is the difference between a data.frame and a tibble? {-}

Both are objects that hold data. The data.frame is the structure supported by basic R and the tibble is an extended variant that is supported by the tidyverse package. Dependig on the function that is used to load data, `read.csv()` from base R or `read_csv()` from the tidyverse, the data will be loaded in a data.frame or tibble, respectively. It is possible to convert a classic data.frame to a tibble (which requires the tidyverse pakcage):
```{r}
df <- as_tibble(mtcars)
class(df)
```
And to convert a tibble to a data.frame:
```{r}
df <- as.data.frame(df)
class(df)
```

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### What's up with spaces in variable names and in files names? {-}

Spaces are used to separate words (as in this line). When a space would be used between two words, these would be treated as separate entities. Avoiding spaces in filenames has a more technical background. Most filesystems currently accept spaces, but some systems do not. To increase compatibility across systems it is a good habit to use_underscores_instead.

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### What are the rules for naming dataframes or variables? {-}

Do not use spaces, stick to characters and numbers. Whenever a variable consists of multiple words, e.g. room temperature there are two options:

1. Add an underscore as separator: `room_temperature.`
2. Use the 'camelCase' notation: `roomTemperature.`

Personally, I prefer an underscore and the abbreviation df for dataframe when multiple dataframes are generated, e.g. df_tidy or df_summary

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### What is the difference between `<-` and `=` for assigning variables? {-}

R prefers the `<-` for the assignment of a value to a variable. In RStudio the shortcut is `<alt>+<->`. It really is a _preference_ since both can be used:
```{r}
x <- 1
y = 2
x + y
```
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### What does 'NA' mean in a dataframe? {-}

When no data is available, this is known as a 'missing value'. In R this is indicated with NA for 'Not Available'. Empty cells in a CSV file will be converted to NA when the file is loaded. Other characters that can be present in a file (especially xls files) are: "." or "NaN" or "#N/A" or "#VALUE!". To convert these strings to NA use:
```{r}
df <- read.csv('FPbase_Spectra.csv', na.strings=c(".", "NaN", "#N/A", "#VALUE!"))
```

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### What is the beste way to type a '%>%' operator? {-}

I prefer to literally type it. The shortcut that works in Rstudio is `<shift>+<command>+<M>` or `<shift>+<control>+<M>`.

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### Where do I find the example data? {-}

The example data that is used in Chapter 2 and 3 is located on this github page: [https://github.com/JoachimGoedhart/DataViz-protocols](https://github.com/JoachimGoedhart/DataViz-protocols)

The data that is used for the protocols in Chapter 4 is located in the subdirectory [/Protocols](https://github.com/JoachimGoedhart/DataViz-protocols/tree/main/Protocols).

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### Is there a way to re-use or adjust the protocols? {-}

Instead of copy-pasting and running the code line-by-line, you can download the R Markdown file (.Rmd) from the [protocols folder](https://github.com/JoachimGoedhart/DataViz-protocols/tree/main/Protocols) in the Github repository. The R Markdown file (together with the data) can be used to replicate the protocol and to modify it. For more info on R Markdown, see [https://rmarkdown.rstudio.com](https://rmarkdown.rstudio.com)

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### Which packages are included in the `{tidyverse}` package? {-}

You can find this out by first loading the package and then run `tidyverse_packages()`

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### What is the difference between `require()` and `library()` for loading a package? {-}

Both functions can be used to load a package. The difference is that `require()` returns `FALSE` when the package does not exist and can be used to check whether a package was loaded:

```{r}
if (require("nonexistant") == FALSE) ("This packkage doesn't exist")
```

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### Is it possible to have interactive file selection? {-}

In some cases it can be convenient to select a file by point-and-click, although this is not strictly reproducible. This example code shows how this can be achieved by using the function `file.choose()` inside a function for reading a csv file:

```{r eval = FALSE}
df <- read.csv(file.choose(), header = TRUE)
```

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### {-}