Computation

Author
Affiliation

Chung-hong Chan

GESIS

Published

2023-06-19

Markdown table

| City     | Country |
|----------|---------|
| Mannheim | Germany |
| Paris    | France  |
| Tokyo    | Japan   |
City Country
Mannheim Germany
Paris France
Tokyo Japan

Exercise

Create a Tic Tac Toe field and play a game with yourself

X X O
O O X
X O O

Code chunks

Literate programming: mixing a document formatting language and a programming language.

Code chunks are snippets of programming language to do the “mixing”. You can insert a code chunk in a Quarto document with (at least) three backticks.


```r
x <- "Hello World!"
message(x)
```

```python
x = "Hello World!"
print(x)
```

```c
int main() {
    printf("Hello World!");
    return 0;
}
```

Exercise 1

Copy and paste the R code chunk into a Quarto document and render it. Tell us what’s the output.

Exercise 2 (Optional)

This workshop is really not about R, but we still need to use R. If you don’t know (enough) R, try to familiarize yourself with the following. If you know all of them, congratulations you know enough R to survive this session!

1 + 2 - 3 * 4 / 3

x <- "hello world"

x

## message

message(x)

## mtcars is a built-in dataset. The data structure is called data frame
mtcars

## simple functions
nrow(mtcars)

head(mtcars)

## basic viz

plot(mtcars$mpg, mtcars$hp)

hist(mtcars$mpg)

## installing external packages

install.packages("knitr")

## You can either call the package by `library`

library(knitr)
kable

## or the namespace operator ::

knitr::kable

## read some data, if your csv file is called hello.csv

x <- read.csv("hello.csv")

## get help

?read.csv

Computation Option 1: Executable Code chunk

The way to insert a code chink in the previous exercise does not involve code execution. Therefore, Quarto will only format the code, e.g. add syntax highlight.

To make the code executable, wrap r with a pair of curly.


```{r}
x <- "Hello World!"
message(x)
```

Exercise 1

Copy and paste the R code chunk into a Quarto document and render it. Tell us what’s the output.


```{r}
x <- "Hello World!"
message(x)
```

Exercise 2

Create a code chunk in a Quarto document to calculate the area of a circle with radius = 10 (hints: pi). Render it.

Computation Option 2: Inline R code (knitr)

Another way to invoke code execution is to use inline code: `r `

## Mathematics

I don't know the answer of 1 + 1 equals to 2.

When to use inline?

For quick and dirty generation of one number in a paragraph, e.g. number of observations, calculation of mean. Otherwise, use code chunk.

Exercise 1:

Convert the above area calculation to inline R code.

Exercise 2:

Write inline R code to display the following sentence (hints: nrow):

There are 32 observations in the data frame mtcars.

Full circle

Some R functions generate Markdown code.

mtcars
knitr::kable(mtcars)

Exercise

Display the content of mtcars as a table in a Quarto document like the following:

mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2

Figures

```{r}
hist(mtcars$mpg)
```

Exercise

Display a scatter plot in a Quarto document like the following:

Execution Options

You can control how the code is executed with execution options

Output options (knitr)


```{r}
#| echo: false
knitr::kable(mtcars)
```

There are

  • eval (evaluate the code chunk or not)
  • echo (include the source code or not in the output)
  • output (include the execution result in the output or not: true, false, asis)
  • warning (include warnings in the output)
  • error (include errors in the output)
  • include (include: false suppresses all output, useful for reading data or loading packages)

Exercise

Read this file and make Quarto display the following:

There are 344 observations in the file penguins_raw.csv and the first few rows look like so:

studyName Sample.Number Species Region Island Stage Individual.ID Clutch.Completion Date.Egg Culmen.Length..mm. Culmen.Depth..mm. Flipper.Length..mm. Body.Mass..g. Sex Delta.15.N..o.oo. Delta.13.C..o.oo. Comments
PAL0708 1 Adelie Penguin (Pygoscelis adeliae) Anvers Torgersen Adult, 1 Egg Stage N1A1 Yes 2007-11-11 39.1 18.7 181 3750 MALE NA NA Not enough blood for isotopes.
PAL0708 2 Adelie Penguin (Pygoscelis adeliae) Anvers Torgersen Adult, 1 Egg Stage N1A2 Yes 2007-11-11 39.5 17.4 186 3800 FEMALE 8.94956 -24.69454 NA
PAL0708 3 Adelie Penguin (Pygoscelis adeliae) Anvers Torgersen Adult, 1 Egg Stage N2A1 Yes 2007-11-16 40.3 18.0 195 3250 FEMALE 8.36821 -25.33302 NA
PAL0708 4 Adelie Penguin (Pygoscelis adeliae) Anvers Torgersen Adult, 1 Egg Stage N2A2 Yes 2007-11-16 NA NA NA NA NA NA NA Adult not sampled.
PAL0708 5 Adelie Penguin (Pygoscelis adeliae) Anvers Torgersen Adult, 1 Egg Stage N3A1 Yes 2007-11-16 36.7 19.3 193 3450 FEMALE 8.76651 -25.32426 NA
PAL0708 6 Adelie Penguin (Pygoscelis adeliae) Anvers Torgersen Adult, 1 Egg Stage N3A2 Yes 2007-11-16 39.3 20.6 190 3650 MALE 8.66496 -25.29805 NA

Figure Options (knitr)

ref

There are:

  • fig-width
  • fig-height
  • fig-cap
  • fig-alt
  • fig-align
  • fig-dpi

An example to play around


```{r}
#| fig-cap: "A random histogram"
#| fig-height: 10
#| fig-align: right
#| echo: false
hist(mtcars$mpg)
```

A random histogram

Best practices

Label your chunk

It does nothing apparently. You will know why it is important tomorrow. All labels must be unique.

```{r}
#| label: mtcars_listing
#| echo: false
knitr::kable(mtcars)
```

(Not) cache

You can cache the computational result of a chunk (save the result as a file. When the Quarto file is being rendered again, the cached result is used instead of doing the computation again). It’s best to use it with a labeled code chunk. In general, it is not recommended for a reproducible scientific workflow. Use it unless you know what you are doing.

```{r}
#| label: mtcars_listing
#| echo: false
#| cache: true
knitr::kable(mtcars)
```

Engines

R code inside a Quarto document is handled by the computational engine knitr. You might want to use another computational engine if R is not your thing. For example, Python code is handled by Jupyter. In a mix language environment, you might need reticulate.


```{python}
## This is all the Python I know

def fib(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b
list(fib(5))
```
## This is all the Python I know

def fib(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b
list(fib(5))
[0, 1, 1, 2, 3]

Debrief

Q: How to display table caption?

A:

With computation


```{r}
#| echo: false
#| tbl-cap: "Just a few rows"
#| tbl-cap-location: bottom
#| label: headmtcars
knitr::kable(head(mtcars))
```
Just a few rows
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1

Without computation

| City     | Country |
|----------|---------|
| Mannheim | Germany |
| Paris    | France  |
| Tokyo    | Japan   |

: List of cities
List of cities
City Country
Mannheim Germany
Paris France
Tokyo Japan

Q: I’ve heard that the knitr::kable call is not necessary.

A: You are right. Quarto (or the rendering engine: knitr) can convert all data.frame objects to Markdown tables using the df-print document option. You will learn about document options a.k.a. YAML Front Matter in the next session.

Q: Does interactive viz work?

A: Oui.

```{r}
#| echo: false
#| fig-height: 2
#| fig-width: 5
#| label: ggplotly_demo
library(ggplot2)
library(plotly)
fig <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
ggplotly(fig, height = 600, width = 1000)
```

Q: Any fancy stuff I can do with the code listing?

A: Many

Showing the filename

```{r}
#| eval: false
#| filename: "whatever.R"
library(ggplot2)
library(plotly)
fig <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
ggplotly(fig, height = 600, width = 1000)
```
whatever.R
library(ggplot2)
library(plotly)
fig <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
ggplotly(fig, height = 600, width = 1000)

Code folding

```{r}
#| eval: false
#| code-fold: true
#| code-summary: "Demo ggplotly"
library(ggplot2)
library(plotly)
fig <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
ggplotly(fig, height = 600, width = 1000)
```
Demo ggplotly 
library(ggplot2)
library(plotly)
fig <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
ggplotly(fig, height = 600, width = 1000)

Line-numbering

```{r}
#| eval: false
#| code-line-numbers: true
library(ggplot2)
library(plotly)
fig <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
ggplotly(fig, height = 600, width = 1000)
```
library(ggplot2)
library(plotly)
fig <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
ggplotly(fig, height = 600, width = 1000)

And many more.