Lab 2: Import and visualize data

Not graded, just practice

Author

Katie Schuler

Published

September 7, 2023

1 Tidyverse

What is the relationship between tidyverse and readr?

tidyverse is a package in the readr family of packages readr is a package in the tidyverse family of packages tidyverse and readr are two unrelated packages tidyverse and reader are two names for the same package

In the tidyverse, what does “tidy data” refer to?

any data we load into the tidyverse a dataset with no missing values a standard way to organize a dataset the process of cleaning a dataset

What is the purpose of the purrr package?

What is the primary purpose of the readr package?

Which of the following returned this message?

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(tidyverse) family(tidyverse) library.collection(tidyverse) library(tidyverse, report=TRUE)

2 purrr

Suppose we have the following tibble, stored with the variable df. What will map(df, mean) return?

# A tibble: 4 × 3
      x     y     z
  <int> <int> <int>
1     1     5     9
2     2     6    10
3     3     7    11
4     4     8    12

the mean of each row the mean of each column the mean of all values Error: cannot compute mean of type integer

Suppose we wanted to coerce each column in the previous tibble to the data type double with one line of code. Fill in the two arguments to map that would accomplish this:

map(, )

3 Tibbles

Suppose we run the following code block. What will is.data.frame(tib) return?

tib <- tibble(x = 1:2, y = c("a", "b"))

True False

What will typeof(tib) return?

Which of the following would convert a dataframe, df, to a tibble?

Suppose we run the following code, what will is_tibble() return?

x <- tribble(
    ~x, ~y, 
    2, 3, 
    4, 5
)

True False

Suppose we create the following tibble, tib, what will tib$a return?

# A tibble: 4 × 3
    age name   alt_name
  <dbl> <chr>  <chr>   
1     1 dory   dolores 
2     2 hazel  <NA>    
3     3 graham <NA>    
4     5 joan   joanie

a warning and the value NULL age via partial matching age and alt_name via partial matching hazel, graham, joan, and joanie via partial matching an empty vector

4 readr

Many questions below refer to this dataset, borrowed from R4DS and available at the url https://pos.it/r4ds-students-csv.

Figure 1: borrowed from R for Data Science

What does the csv in read_csv() stand for? Fill in the blank.

separated values

Suppose we attempt to import the csv file given above with the code below. What will be the result?

data <- read_csv("https://pos.it/r4ds-students-csv",
    col_types = list(AGE = col_double())
)

imports with no errors or warnings fails to import, throws error imports, but with a warning that there are parsing issues imports, but changes the column name to age

Suppose we import the dataset given above and name it data. What will is.na(data[3,3]) return?

True False

Suppose we import the dataset given above and name it data. Which of the following would return the first column?

data[1] data[[1]] data[[Student ID]] data$`Student ID`

True or false, assuming the same dataset the following code would rename the Student ID column to student_id?

data %>% rename(student_id = `Student ID`)

True False

True or false, we can use a read_*() function from readr to import a google sheet.

True False

5 Data visualization

We will continue working with the ratings dataset from the visualization lecture (part of the languageR package). It contains the following variables:

Rows: 81
Columns: 14
$ Word             <fct> almond, ant, apple, apricot, asparagus, avocado, badg…
$ Frequency        <dbl> 4.204693, 5.347108, 6.304449, 3.828641, 3.663562, 3.4…
$ FamilySize       <dbl> 0.0000000, 1.3862944, 1.0986123, 0.0000000, 0.0000000…
$ SynsetCount      <dbl> 1.0986123, 1.0986123, 1.0986123, 1.3862944, 1.0986123…
$ Length           <int> 6, 3, 5, 7, 9, 7, 6, 6, 3, 6, 3, 8, 10, 9, 8, 5, 9, 5…
$ Class            <fct> plant, animal, plant, plant, plant, plant, animal, pl…
$ FreqSingular     <int> 24, 69, 315, 26, 19, 24, 53, 74, 155, 37, 118, 15, 26…
$ FreqPlural       <int> 42, 140, 231, 19, 19, 6, 78, 77, 103, 14, 180, 19, 31…
$ DerivEntropy     <dbl> 0.0000, 0.5620, 0.4960, 0.0000, 0.0000, 0.0000, 0.634…
$ Complex          <fct> simplex, simplex, simplex, simplex, simplex, simplex,…
$ rInfl            <dbl> -0.54232429, -0.70026465, 0.30900484, 0.30010459, 0.0…
$ meanWeightRating <dbl> 1.4860, 3.3489, 2.1948, 1.3216, 1.4424, 1.3256, 3.047…
$ meanSizeRating   <dbl> 1.8912, 3.6275, 2.4730, 1.7597, 1.8660, 1.7737, 3.369…
$ meanFamiliarity  <dbl> 3.72, 3.60, 5.84, 4.40, 3.68, 4.12, 2.12, 5.68, 3.20,…

Fill in the blanks below with one of the following words: data, aesthetics, geom.

The basic ggplot involves: (1) using your , (2) defining how variables are mapped to visual properties (), and (3) determining the geometrical object that a plot uses to represent data ()

When ggplot2 maps a categorical variable to an aesthetic, it automatically assigns a unique value of the aesthetic to each level of the variable. What is this process called?

level assignment variable aestheticization autofill scaling

The code below generated which of the following figures?

ggplot(
    data = ratings,
    mapping = aes(x = Frequency, y = meanFamiliarity)
) + 
    geom_point(mapping = aes(color = Class)) +
    geom_smooth(method = "lm") +
    theme_classic(base_size=20)

A B C

Suppose we want to map the variable Complex to the color aesthetic in a scatterplot. Which of the following arguments could we pass to geom_point()?

color = Complex mapping=aes(color = Complex) color = mapping(Complex) aes(color=Complex)

Which geoms are depicted in the following figure?

Which geoms are depicted in the following figure?