Danish Kings

The task here is to load your Danish Monarchs csv into R using the tidyverse toolkit, calculate and explore the kings’ duration of reign with pipes %>% in dplyr and plot it over time.

Load the kings

Make sure to first create an .Rproj workspace with a data/ folder where you place either your own dataset or the provided kings.csv dataset.

1. Look at the dataset that are you loading and check what its columns are separated by? (hint: open it in plain text editor to see)

2. Create a kings object in R with the different functions below and inspect the different outputs.

• read.csv()
• read_csv()
• read.csv2()
• read_csv2()

# FILL IN THE CODE BELOW and review the outputs

kings1 <- read.csv("data/Danish_kings")
kings2 <- read_csv("data/Danish_kings")
kings3 <- read.csv2("data/Danish_kings")
kings4 <- read_csv2("data/Danish_kings")

Answer: 1. Which of these functions is a tidyverse function? Read data with it below into a kings object

read_csv() and read_csv2() is a part of the tidyverse-package (specifically readr). read.csv() and read.csv2() belongs to base R.

2. What is the result of running class() on the kings object created with a tidyverse function. class(kings4)

[1] “tbl_df” “tbl” “data.frame”

3. How many columns does the object have when created with these different functions?

kings1 <- read_csv2(“data/Danish_kings”)
kings2 <- read_csv2(“data/Danish_kings”)
kings3 <- read_csv2(“data/Danish_kings”)
kings4 <- read_csv2(“data/Danish_kings”)

There is 11 columns

4. Show the dataset so that we can see how R interprets each column

glimpse(Danish_kings.csv) View(Danish_kings.csv)

# COMPLETE THE BLANKS BELOW WITH YOUR CODE, then turn the 'eval' flag in this chunk to TRUE.

kings <- Danish_kings

class(kings)


glimpse(kings)


View(kings)

Calculate the duration of reign for all the kings in your table

You can calculate the duration of reign in years with mutate function by subtracting the equivalents of your startReign from endReign columns and writing the result to a new column called duration. But first you need to check a few things:

• Is your data messy? Fix it before re-importing to R
• Do your start and end of reign columns contain NAs? Choose the right strategy to deal with them: na.omit(), na.rm=TRUE, !is.na()

Create a new column called duration in the kings dataset, utilizing the mutate() function from tidyverse. Check with your group to brainstorm the options.

The code I used

kings <- kings %>%
  filter(!is.na(start_reign) & !is.na(end_reign))
kings <- kings %>%
  mutate(duration = end_reign - start_reign)
glimpse(kings)

Calculate the average duration of reign for all rulers

Do you remember how to calculate an average on a vector object? If not, review the last two lessons and remember that a column is basically a vector. So you need to subset your kings dataset to the duration column. If you subset it as a vector you can calculate average on it with mean() base-R function. If you subset it as a tibble, you can calculate average on it with summarize() tidyverse function. Try both ways!

• You first need to know how to select the relevant duration column. What are your options?
• Is your selected duration column a tibble or a vector? The mean() function can only be run on a vector. The summarize() function works on a tibble.
• Are you getting an error that there are characters in your column? Coerce your data to numbers with as.numeric().
• Remember to handle NAs: mean(X, na.rm=TRUE)

The code I used

kings %>%
  summarise(avg_duration = mean(duration, na.rm = TRUE))

The average duration of reign for all rulers was 20.2 years

How many and which kings enjoyed a longer-than-average duration of reign?

You have calculated the average duration above. Use it now to filter() the duration column in kings dataset. Display the result and also count the resulting rows with count()

The code I used

long_reign_kings <- kings %>%
  filter(duration > average_duration)
long_reign_kings %>% count()
print(long_reign_kings)

24 kings enjoyed a longer-than-average duration of reign

How many days did the three longest-ruling monarchs rule?

• Sort kings by reign duration in the descending order. Select the three longest-ruling monarchs with the slice() function
• Use mutate() to create Days column where you calculate the total number of days they ruled
• BONUS: consider the transition year (with 366 days) in your calculation!

#The code I used

top_3_kings <- kings %>%
  arrange(desc(duration)) %>%
  slice(1:3) %>%
  mutate(days = duration * 365.25)
print(top_3_kings)
glimpse(top_3_kings)
21915.00+18993.00+15705.75

The answer is 56613 days

And to submit this rmarkdown, knit it into html. But first, clean up the code chunks, adjust the date, rename the author and change the eval=FALSE flag to eval=TRUE so your script actually generates an output. Well done!