Whitespace

This lesson is called Whitespace, part of the Data Cleaning with R course. This lesson is called Whitespace, part of the Data Cleaning with R course.

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Your Turn

Solution

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####               Whitespace - your turn               ####
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# - Import the Marine Protected Areas data (MPAS-your.csv) from the previous lesson
# - check the Country variable for leading or trailing whitespace
# - Remove it if necessary.

# load packages -----------------------------------------------------------
library(readr)
library(stringr)
library(dplyr)

# import data -------------------------------------------------------------
MPAs <- read_csv("data/MPAS-your.csv", trim_ws = FALSE)


# check for whitespace ----------------------------------------------------
MPAs %>%
  mutate(
    leading_ws = str_detect(Country, "^ "),
    trailing_ws = str_detect(Country, " $")
  ) %>%
  select(Country, leading_ws, trailing_ws)

# remove whitespace -------------------------------------------------------
MPAs <- MPAs %>% mutate(Country = str_squish(Country))

# check if whitespace was removed
MPAs %>%
  mutate(
    leading_ws = str_detect(Country, "^ "),
    trailing_ws = str_detect(Country, " $")
  ) %>%
  select(Country, leading_ws, trailing_ws)

In the Marine Protected Areas dataset from the previous lesson (MPAS-your.csv), check the Country variable for leading or trailing whitespace and remove it if necessary.

Whitespace

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