CourseKata - ckcode-chapter-a2-understanding-data

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ckcode ⌲ chapter-a2-understanding-data

require(coursekata)

# Here's how to combine nine 2s into a vector
# You could also use rep(2, times = 9)
bunch_of_2s <- c(2, 2, 2, 2, 2, 2, 2, 2, 2)

# Create a vector called bunch_of_123s with the numbers
# 2, 1, 3, 3, 2, 3, 1, 2, 1
bunch_of_123s <- c()

# Here's how to combine nine 2s into a vector
# You could also use rep(2, times = 9)
bunch_of_2s <- c(2, 2, 2, 2, 2, 2, 2, 2, 2)

# Create a vector called bunch_of_123s with the numbers
# 2, 1, 3, 3, 2, 3, 1, 2, 1
bunch_of_123s <- c(2, 1, 3, 3, 2, 3, 1, 2, 1)

ex() %>% check_object("bunch_of_123s") %>% check_equal()

CK Code: ch2-1

require(coursekata)

# Here is code to create the vector that we named bunch_of_2s
bunch_of_2s <- c(2,2,2,2,2,2,2,2,2)

# Now, let's run the tally() function on bunch_of_2s

# Here is code to create the vector that we named bunch_of_2s
bunch_of_2s <- c(2,2,2,2,2,2,2,2,2)

# Now, let's run the tally() function on bunch_of_2s
tally(bunch_of_2s)

ex() %>% check_function("tally") %>% check_result() %>% check_equal()

CK Code: ch2-2

require(coursekata)
MindsetMatters <- Lock5withR::MindsetMatters %>%
    mutate(Condition = factor(Cond, levels = c(1, 0), labels = c("Informed", "Uninformed")))

# Try typing MindsetMatters to see what is in the data frame.

MindsetMatters

ex() %>%
    check_output_expr("MindsetMatters")

CK Code: ch2-3

require(coursekata)
MindsetMatters <- Lock5withR::MindsetMatters %>%
    mutate(Condition = factor(Cond, levels = c(1, 0), labels = c("Informed", "Uninformed")))

# Run this code to get the first 6 rows of MindsetMatters
head(MindsetMatters)

# Run this code to get the first 6 rows of MindsetMatters
head(MindsetMatters)

ex() %>%
    check_function("head") %>%
    check_result() %>%
    check_equal()

CK Code: ch2-4

require(coursekata)
MindsetMatters <- Lock5withR::MindsetMatters %>%
    mutate(Condition = factor(Cond, levels = c(1, 0), labels = c("Informed", "Uninformed")))

# Run this code to see the structure of MindsetMatters
str(MindsetMatters)

str(MindsetMatters)

ex() %>%
    check_function("str") %>%
    check_result() %>%
    check_equal()

CK Code: ch2-5

require(coursekata)
MindsetMatters <- Lock5withR::MindsetMatters %>%
    mutate(Condition = factor(Cond, levels = c(1, 0), labels = c("Informed", "Uninformed")))

# Use the $ sign to print out the contents of the Age variable in the MindsetMatters data frame

# Use the $ sign to print out the contents of the Age variable in the MindsetMatters data frame
MindsetMatters$Age

ex() %>%
    check_output_expr("MindsetMatters$Age", missing_msg = "Have you used $ to select the Age variable in MindsetMatters?")

CK Code: ch2-27

require(coursekata)
MindsetMatters <- Lock5withR::MindsetMatters %>%
    mutate(Condition = factor(Cond, levels = c(1, 0), labels = c("Informed", "Uninformed")))

# Use tally() with the MindsetMatters data frame to create a frequency table of housekeepers by Condition

# Use tally() with the MindsetMatters data frame to create a frequency table of housekeepers by Condition
tally(~Condition, data = MindsetMatters)

# Another solution
# tally(MindsetMatters$Condition)

ex() %>%
    check_function("tally") %>%
    check_result() %>%
    check_equal()

CK Code: ch2-6

require(coursekata)
MindsetMatters <- Lock5withR::MindsetMatters %>%
    mutate(Condition = factor(Cond, levels = c(1, 0), labels = c("Informed", "Uninformed")))

# save MindsetMatters, arranged by Age, back to MindsetMatters
arrange(MindsetMatters, Age)

# write code to print out the first 6 rows of MindsetMatters

# save MindsetMatters, arranged by Age, back to MindsetMatters
MindsetMatters <- arrange(MindsetMatters, Age)

# write code to print out the first 6 rows of MindsetMatters
head(MindsetMatters)

no_save <- "Make sure to both `arrange()` `MindsetMatters` by `Age` *and* save the arranged data frame back to `MindsetMatters`."
ex() %>% {
    check_object(., "MindsetMatters") %>% check_equal(incorrect_msg = no_save)
    check_function(., "arrange") %>% check_arg("...") %>% check_equal()
    check_function(., "head") %>% check_result() %>% check_equal()
}

CK Code: ch2-7

require(coursekata)
MindsetMatters <- Lock5withR::MindsetMatters %>%
    mutate(Condition = factor(Cond, levels = c(1, 0), labels = c("Informed", "Uninformed")))

# arrange MindsetMatters by Wt in descending order
MindsetMatters <-

# write code to print out a few rows of MindsetMatters

# arrange MindsetMatters by Wt in descending order
MindsetMatters <- arrange(MindsetMatters, desc(Wt))

# write code to print out a few rows of MindsetMatters
head(MindsetMatters)

no_save <- "Did you save the arranged data set back to `MindsetMatters`?"
ex() %>% {
    check_function(., "desc") %>%
        check_arg("x") %>%
        check_equal(eval = FALSE)
    check_function(., "arrange") %>%
        check_arg(".data") %>%
        check_equal(eval = FALSE)
    check_object(., "MindsetMatters") %>%
        check_equal(incorrect_msg = no_save)
    check_function(., "head") %>%
        check_arg("x") %>%
        check_equal()
}

CK Code: ch2-8

require(coursekata)
Fingers <- Fingers %>%
    mutate_if(is.factor, as.numeric) %>%
    arrange(desc(Sex)) %>%
    {.[1, "FamilyMembers"] <- 2; . } %>%
    {.[1, "Height"] <- 62; . }

# A way to look at a data frame is to type its name
# Look at the data frame called Fingers

Fingers

ex() %>% check_output_expr("Fingers")

CK Code: ch2-9

require(coursekata)
Fingers <- Fingers %>%
    mutate_if(is.factor, as.numeric) %>%
    arrange(desc(Sex)) %>%
    {.[1, "FamilyMembers"] <- 2; . } %>%
    {.[1, "Height"] <- 62; . }

# Remember the head() command?
# Use it to look at the first six rows of Fingers

head(Fingers)

ex() %>% check_output_expr("head(Fingers)", missing_msg = "Did you call `head()` with `Fingers`?")

CK Code: ch2-10

require(coursekata)
Fingers <- Fingers %>%
    mutate_if(is.factor, as.numeric) %>%
    arrange(desc(Sex)) %>%
    {.[1, "FamilyMembers"] <- 2; . } %>%
    {.[1, "Height"] <- 62; . }

# Try it and see what happens
head(Fingers, 3)

head(Fingers, 3)

ex() %>% check_function("head") %>% check_arg("n") %>% check_equal()

CK Code: ch2-11

require(coursekata)
Fingers <- Fingers %>%
    mutate_if(is.factor, as.numeric) %>%
    arrange(desc(Sex)) %>%
    {.[1, "FamilyMembers"] <- 2; . } %>%
    {.[1, "Height"] <- 62; . }

# Try using tail() to look at the last 6 rows of the Fingers data frame.

tail(Fingers)

ex() %>% check_function("tail") %>% check_result() %>% check_equal()

CK Code: ch2-12

require(coursekata);
allow_solution_error()

Fingers <- Fingers %>%
    mutate_if(is.factor, as.numeric) %>%
    arrange(desc(Sex)) %>%
    {.[1, "FamilyMembers"] <- 2; . } %>%
    {.[1, "Height"] <- 62; . }

# this turns Sex into a factor:
Fingers$Sex <- factor(Fingers$Sex)

# click <submit>: this code will produce an error because you can't sum a factor
sum(Fingers$Sex)

# this turns Sex into a factor:
Fingers$Sex <- factor(Fingers$Sex)

# click <submit>: this code will produce an error because you can't sum a factor
sum(Fingers$Sex)

ex() %>%
  check_function("sum") %>%
  check_output("not meaningful for factors")

CK Code: ch2-13

require(coursekata)
Fingers <- Fingers %>%
    mutate_if(is.factor, as.numeric) %>%
    arrange(desc(Sex)) %>%
    {.[1, "FamilyMembers"] <- 2; . } %>%
    {.[1, "Height"] <- 62; . }

# Interest has been coded numerically in the Fingers data.frame
# Modify the following to convert it to factor and store it as InterestFactor in Fingers
Fingers$InterestFactor <-

Fingers$InterestFactor <- factor(Fingers$Interest)

ex() %>%
    check_object("Fingers") %>%
    check_column("InterestFactor") %>%
    check_equal()

CK Code: ch2-14

require(coursekata)
fake_pop <- rep(0:9, each = 100)

# This takes a random sample of 10 numbers
# from fake_pop and saves them in random_sample
random_sample <- sample(fake_pop, 10)

# This makes a histogram of your sample
gf_histogram(~ random_sample, binwidth=1) +
  scale_x_continuous(limits = c(-.5, 9.5), breaks = c(0:9))


random_sample <- sample(fake_pop, 10)

# this will make a histogram of your sample
gf_histogram(~ random_sample, binwidth=1) +
  scale_x_continuous(limits = c(-.5, 9.5), breaks = c(0:9))

ex() %>% {
    check_object(., "random_sample")
    check_function(., "gf_histogram")
}

CK Code: ch2-17

require(coursekata)

# Run this code
select(Fingers, Sex, Thumb)

select(Fingers, Sex, Thumb)

ex() %>% check_output_expr("select(Fingers, Sex, Thumb)")

CK Code: ch2-28

require(coursekata)

# Write the code select(Fingers, Sex, Thumb) inside of head()
# as shown in the .gif above
head()

head(select(Fingers, Sex, Thumb))

ex() %>% check_or(
    check_correct(
        check_function(., "head") %>% check_result() %>% check_equal(),
        check_correct(
            check_function(., "select") %>% check_result() %>% check_equal(),
            check_function(., "select") %>% {
                check_arg(., ".data") %>% check_equal(incorrect_msg = "Did you specify the Fingers data frame?")
                check_arg(., "...", arg_not_specified_msg = "Did you include the column names?") %>% check_equal(incorrect_msg = "Did you select the Sex and Thumb columns?")
            }
        )
    ),
    override_solution(., "head(select(Fingers, Thumb, Sex))") %>%
        check_correct(
            check_function(., "head") %>% check_result() %>% check_equal(),
            check_correct(
                check_function(., "select") %>% check_result() %>% check_equal(),
                check_function(., "select") %>% {
                    check_arg(., ".data") %>% check_equal(incorrect_msg = "Did you specify the Fingers data frame?")
                    check_arg(., "...", arg_not_specified_msg = "Did you include the column names?") %>% check_equal(incorrect_msg = "Did you select the Thumb and Sex columns?")
                }
            )
        )
)

CK Code: ch2-29

require(coursekata)

# Run this code
filter(Fingers, Thumb == 66)

filter(Fingers, Thumb == 66)

ex() %>% check_output_expr("filter(Fingers, Thumb == 66)")

CK Code: ch2-30

require(coursekata)

# Arrange SSLast in descending order
Fingers <-

# Print out just the variable SSLast from the Fingers data frame

Fingers <- arrange(Fingers, desc(SSLast))
Fingers$SSLast

ex() %>% {
    check_function(.,"arrange")
    check_function(., "desc")
    check_object(., "Fingers") %>% check_equal()
    check_output_expr(., "Fingers$SSLast")
}

CK Code: ch2-18

require(coursekata)
Fingers <- Fingers %>%
    arrange(desc(SSLast))

# Filter out the students who have missing data for SSLast
Fingers_subset <-

# Print out the variable SSLast from Fingers_subset

Fingers_subset <- filter(Fingers, SSLast != "NA")
Fingers_subset$SSLast

ex() %>% {
    check_function(., "filter") %>% {
        check_arg(., ".data") %>% check_equal()
        check_arg(., "...") %>% check_equal()
        check_result(.) %>% check_equal()
    }
    check_or(.,
        check_output_expr(., "Fingers_subset$SSLast"),
        override_solution(., 'Fingers_subset <- filter(Fingers, SSLast != "NA"); select(Fingers_subset, SSLast)') %>%
          check_function("select") %>%
          check_result() %>%
          check_equal()
    )
}

CK Code: ch2-19

require(coursekata)
Fingers$RingLonger <- Fingers$Ring > Fingers$Index

# This code creates a variable called RingLonger
Fingers$RingLonger <- Fingers$Ring > Fingers$Index

# Write code to tally up RingLonger in Fingers.

# Either of these:
tally(Fingers$RingLonger)
tally(~RingLonger, data = Fingers)

ex() %>% check_correct(
    check_function(., "tally") %>% check_result() %>% check_equal(),
    {
        check_error(.)
        check_function(., "tally") %>% check_arg("x") %>% check_equal(incorrect_msg = "Make sure you are getting RingLonger from Fingers using the $.")
    }
)

CK Code: ch2-20

require(coursekata)

# Write code to create this summary variable
Fingers$IndexRingRatio <-

# Will this print anything?

Fingers$IndexRingRatio <- Fingers$Index / Fingers$Ring

ex() %>% check_object("Fingers") %>% check_column("IndexRingRatio") %>% check_equal()

CK Code: ch2-21

require(coursekata)
Fingers <- Fingers %>%
    mutate(IndexRingRatio = Index/Ring)

# Use head() and select() together to look at the first six rows of Ring, Index, and IndexRingRatio

head(select(Fingers, Ring, Index, IndexRingRatio))

# These also work:
# select(Fingers, Ring, Index, IndexRingRatio) %>% head()
# Fingers %>% select(Ring, Index, IndexRingRatio) %>% head()

check_df <- function(state) {
    check_function(state, "head") %>%
        check_result() %>%
        check_equal()
}
ex() %>% check_or(
    check_df(.),
    override_solution(., "head(select(Fingers, Ring, IndexRingRatio, Index))") %>%
        check_df(.),
    override_solution(., "head(select(Fingers, Index, Ring, IndexRingRatio))") %>%
        check_df(.),
    override_solution(., "head(select(Fingers, Index, IndexRingRatio, Ring))") %>%
        check_df(.),
    override_solution(., "head(select(Fingers, IndexRingRatio, Ring, Index))") %>%
        check_df(.),
    override_solution(., "head(select(Fingers, IndexRingRatio, Index, Ring))") %>%
        check_df(.)
)

CK Code: ch2-21a

require(coursekata)

# This code averages the lengths of the Thumb and Pinkie
# Modify it to find the average length of all five fingers
Fingers$AvgFinger <- (Fingers$Thumb + Fingers$Pinkie)/2

# Write code to look at a few lines of the Fingers data frame

Fingers$AvgFinger <- (Fingers$Thumb + Fingers$Index + Fingers$Middle + Fingers$Ring + Fingers$Pinkie)/5
head(Fingers)

ex() %>% {
    check_object(., "Fingers") %>%
        check_column("AvgFinger") %>%
        check_equal()
    check_function(., "head") %>%
        check_arg("x") %>%
        check_equal()
}

CK Code: ch2-22

require(coursekata)
Fingers <- Fingers %>%
    mutate(Job = as.numeric(Job))

# Save the recoded version of `Job` to `JobRecode`
Fingers$JobRecode <- recode()

# Write code to print the first 6 observations of `Job` and `JobRecode`

Fingers$JobRecode <- recode(Fingers$Job, "1" = 0, "2" = 50, "3" = 100)
head(select(Fingers, Job, JobRecode))

ex() %>% {
    check_object(., "Fingers") %>% check_column("JobRecode") %>% check_equal()
    . %>% check_or(
        check_output_expr(., "head(select(Fingers, Job, JobRecode))"),
        check_output_expr(., "head(select(Fingers, JobRecode, Job))")
    )
}

CK Code: ch2-23

require(coursekata)

# run your code here

CK Code: A2_Code_Review2_01

require(coursekata)

# run your code here

CK Code: A2_Code_Review2_02

require(coursekata)

# run your code here

CK Code: A2_Code_Review2_03

require(coursekata)

# run your code here

CK Code: A2_Code_Review2_04

require(coursekata)

# run your code here

CK Code: A2_Code_Review2_05

require(coursekata)

# run your code here

CK Code: A2_Code_Review2_06

require(coursekata)

# run your code here

CK Code: A2_Code_Review2_07

require(coursekata)

# run your code here

CK Code: A2_Code_Review2_08

ckcode-chapter-a1-welcome-and-r ckcode-chapter-a3-examining-distributions

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ckcode ⌲ chapter-a2-understanding-data

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