r_data_wrangling

Question 1

What library is used for data wrangling in R?

Answer 1

dplyr

Question 2

Create a new variable “rate” that stores the murder rate within the dataset “murders”

Answer 2

• murders <- mutate(murders, rate=total/population*100000)

Question 3

Display only the states where the murder rate (“rate”) is less than .71

Answer 3

• filter(murders,rate <= 0.71)

Question 4

Create a new dataset named “new_table” from the original “murders” dataset, that consists of only the following variables:

• state
• region
• rate

Answer 4

• new_table <- select(murders, state, region, rate)

Question 5

Using “piping”, do the following:

1. Select the following variables:
   
   1. state
   2. region
   3. rate
2. display only those states with a rate less than or equal to .71

Answer 5

• murders %>% select(state,region,rate) %>% filter(rate <= 0.71)

Question 6

What line of code must be added at the end of a data frame creation function (data.frame) in order to make the strings represented as characters

Answer 6

• stringsAsFactors = FALSE

Question 7

Use the function mutate to add a murders column named rate with the per 100,000 murder rate.

Answer 7

• murders <- mutate(murders, rate=total/population*100000)

Question 8

Redefine murders to include a column named rank with the ranks of rate from highest to lowest

Answer 8

• # Redefine murders to include a column named rank with the ranks of rate from highest to lowest
• murders <- mutate(murders, rank = rank(-rate))

Question 9

Use select to only show state names and abbreviations from murders

Answer 9

• # Use “select” to only show state names and abbreviations from murders
• select(murders,state,abb)

Question 10

Filter to show the top 5 states with the highest murder rates

Answer 10

• filter(murders, rank <= 5)

Question 11

Create a new data frame called no_south that removes states from the South region.

How many states are in this category?

Answer 11

1. # Use filter to create a new data frame no_south
   • no_south <- filter(murders, region != “South”)
2. # Use nrow() to calculate the number of rows
   • nrow(no_south)

Question 12

Get unique values within the “region” variable of the “murders” dataset

Answer 12

• unique(murders$region)

Question 13

1. Create a new data frame called murders_nw with only the states from the Northeast and the West.
2. How many states are in this category?

Answer 13

1. # Create a new data frame called murders_nw with only the states from the northeast and the west
   • murders_nw <- filter(murders, region %in% c(“Northeast”, “West”))
2. # Number of states (rows) in this category
   • nrow(murders_nw)

Question 14

1. Add a murder rate column and a rank column as done before
2. Create a table, call it “my_states”, that satisfies both the conditions: it is in the Northeast or West and the murder rate is less than 1.
3. Use select on “my_states” to show only the state name, the rate and the rank

Answer 14

1. # add the rate column
   • murders <- mutate(murders, rate = total / population * 100000, rank = rank(-rate))
2. # Create a table, call it my_states, that satisfies both the conditions
   • my_states <- filter(murders, region %in% c(“Northeast”,”West”) & rate < 1)
3. # Use select to show only the state name, the murder rate and the rank
   • select(my_states, state, rate, rank)

Question 15

In one line:

1. Filter the “murders” dataste to show:
   
   1. states in the Northeast or West
   2. and the murder rate is less than 1.
2. Select only the state name, the rate and the rank

Answer 15

1. # show the result and only include the state, rate, and rank columns, all in one line
   • filter(murders, region %in% c(“Northeast”,”West”) & rate < 1) %>% select(state, rate, rank)

Question 16

Use just one line to create a new data frame, called, my_states that has murder rate and rank column, consider only states in the Northeast or West, which have a murder rate lower than 1 and contain only the state, rate, and rank columns. The line should have four components separated by three %>%.

1. The original dataset murders
2. A call to mutate to add the murder rate and the rank.
3. A call to filter to keep only the states from the Northeast or West and that have a murder rate below 1
4. A call to select that keeps only the columns with the stata name, the murder rate and the rank.

Answer 16

1. # Create new data frame called my_states (with specifications in the instructions)

my_states <- murders %>%

mutate(rate = total / population * 100000, rank = rank(-rate)) %>%

filter(region %in% c(“Northeast”, “West”) & rate < 1) %>%

select(state, rate, rank)