Seaweed Nutrients

Setting up R Packages

library(tidyverse)
library(mosaic)
library(skimr)
library(ggformula)
library(ggbump)
library(ggprism)
library(paletteer) # fancy colour palettes!

Plot Theme

Show the Code

# https://stackoverflow.com/questions/74491138/ggplot-custom-fonts-not-working-in-quarto

# Chunk options
knitr::opts_chunk$set(
  fig.width = 7,
  fig.asp = 0.618, # Golden Ratio
  # out.width = "80%",
  fig.align = "center"
)
### Ggplot Theme
### https://rpubs.com/mclaire19/ggplot2-custom-themes

theme_custom <- function() {
  font <- "Roboto Condensed" # assign font family up front

  theme_classic(base_size = 14) %+replace% # replace elements we want to change

    theme(
      panel.grid.minor = element_blank(), # strip minor gridlines
      text = element_text(family = font),
      # text elements
      plot.title = element_text( # title
        family = font, # set font family
        size = 20, # set font size
        face = "bold", # bold typeface
        hjust = 0, # left align
        # vjust = 2                #raise slightly
        margin = margin(0, 0, 10, 0)
      ),
      plot.subtitle = element_text( # subtitle
        family = font, # font family
        size = 14, # font size
        hjust = 0,
        margin = margin(2, 0, 5, 0)
      ),
      plot.caption = element_text( # caption
        family = font, # font family
        size = 8, # font size
        hjust = 1
      ), # right align

      axis.title = element_text( # axis titles
        family = font, # font family
        size = 10 # font size
      ),
      axis.text = element_text( # axis text
        family = font, # axis family
        size = 8
      ) # font size
    )
}

# Set graph theme
theme_set(new = theme_custom())
#

Introduction

Nine types of Seaweed were rated on different parameters and charted as shown below.

Read the Data

Excel Data

The data is an excel sheet. Inspect it first in Excel and decide which sheet you need, and which part of the data you need. There are multiple sheets! Then use readxl::read_xlsx(..) to read it into R. NOTE: The sheet that contains our data of interest is titled “seaweed nutrition”, range = “A3:R13”.

Inspect the Data

Rows: 10
Columns: 18
$ `common name`     <chr> "RDA", "Norwegian Kelp", "Oarweed", "Thongweed", "Wa…
$ `sci-name`        <chr> NA, "-Ascophyllum nodosum", "-Laminaria digitata", "…
$ `total fats`      <chr> NA, "0.6", "-", "-", "0.6", "0.3", "-", "0.2", "-", …
$ `saturated fat`   <chr> NA, "0.2", "-", "-", "0.1", "0.1", "-", "0", "-", "-"
$ cholesterol       <chr> NA, "0", "0", "0", "0", "0", "0", "0", "0", "-"
$ protein           <chr> NA, "1.7", "-", "-", "3", "5.8", "-", "1.5", "-", "-"
$ `Total fiber`     <dbl> NA, 8.8, 6.2, 9.8, 3.4, 3.8, 5.4, 1.3, 3.8, 4.9
$ `Soluble fiber`   <chr> NA, "7.5", "5.4", "7.7", "2.9", "3", "3", "-", "2.1"…
$ `Insoluble fiber` <chr> NA, "1.3", "0.8", "2.1", "0.5", "1", "2.3", "-", "1.…
$ Carbohydrates     <dbl> NA, 13.1, 9.9, 15.0, 4.6, 5.4, 10.6, 12.0, 4.1, 7.8
$ Calcium           <dbl> NA, 575.0, 364.7, 30.0, 112.3, 34.2, 148.8, 373.8, 3…
$ Potassium         <dbl> NA, 765.0, 2013.2, 1351.4, 62.4, 302.2, 1169.6, 827.…
$ Magnesium         <dbl> NA, 225.0, 403.5, 90.1, 78.7, 108.3, 97.6, 573.8, 46…
$ Sodium            <dbl> NA, 1173.8, 624.6, 600.6, 448.7, 119.7, 255.2, 1572.…
$ Copper            <dbl> NA, 0.8, 0.3, 0.1, 0.2, 0.1, 0.4, 0.1, 0.3, 0.1
$ Iron              <dbl> NA, 14.9, 45.6, 5.0, 3.9, 5.2, 12.8, 6.6, 15.3, 22.2
$ Iodine            <dbl> NA, 18.2, 70.0, 10.7, 3.9, 1.3, 10.2, 6.1, 1.6, 97.9
$ Zinc              <chr> NA, "-", "1.6", "1.7", "0.3", "0.7", "0.3", "-", "0.…

Data Dictionary

Quantitative Variables

Write in.

Qualitative Variables

Write in.

Observations

Write in.

Research Question

Note

Write in! First look at the chart below!

Analyse/Transform the Data

```{r}
#| label: data-preprocessing
#
# Write in your code here
# to prepare this data as shown below
# to generate the plot that follows
```

ABCDEFGHIJ0123456789

common_name <chr>	parameter <chr>	ranks <int>
Norwegian Kelp	calcium_rank	1
Oarweed	calcium_rank	3
Thongweed	calcium_rank	9
Wakame	calcium_rank	6
Nori	calcium_rank	8
Dulse	calcium_rank	5
Irish Moss	calcium_rank	2
Sea Lettuce	calcium_rank	4
Grass kelp	calcium_rank	7
Norwegian Kelp	carbo_rank	2

Plot the Data

Tasks and Discussion

Complete the Data Dictionary.
Select and Transform the variables as shown.
Create the graphs shown and discuss the following questions:
- Identify the type of charts
- Identify the variables used for various geometrical aspects (x, y, fill…). Name the variables appropriately.
- What research activity might have been carried out to obtain the data graphed here? Provide some details.
- What might have been the Hypothesis/Research Question to which the response was Chart?
- Write a 2-line story based on the chart, describing your inference/surprise.
- Based on the diagram, discuss which one an elderly person might try if they are deficient in calcium. If you were trying to avoid carbs, which seaweed sushi would you try?

References

Over 2500 colour palettes are available in the paletteer package. Can you find tayloRswift? wesanderson? harrypotter? timburton?

Here are the Qualitative Palettes:

And the Quantitative/Continuous palettes:

Use the commands:

## For Qual variable-> colour/fill:
scale_colour_paletteer_d(
  name = "Legend Name",
  palette = "package::palette",
  dynamic = TRUE / FALSE
)

## For Quant variable-> colour/fill:
scale_colour_paletteer_c(
  name = "Legend Name",
  palette = "package::palette",
  dynamic = TRUE / FALSE
)