Module 4: Apply 3

Import data

# excel file
data <- read_excel("data/myData.xlsx")
data

## # A tibble: 1,104 × 31
##    town11cd  town11nm population_2011 size_flag rgn11nm coastal coastal_detailed
##    <chr>     <chr>              <dbl> <chr>     <chr>   <chr>   <chr>           
##  1 E34000007 Carlton…            5456 Small To… East M… Non-co… Smaller non-coa…
##  2 E34000016 Dorches…           19060 Small To… South … Non-co… Smaller non-coa…
##  3 E34000020 Ely BUA            19090 Small To… East o… Non-co… Smaller non-coa…
##  4 E34000026 Market …            6429 Small To… Yorksh… Non-co… Smaller non-coa…
##  5 E34000027 Downham…           10884 Small To… East o… Non-co… Smaller non-coa…
##  6 E34000039 Penrith…           15181 Small To… North … Non-co… Smaller non-coa…
##  7 E34000048 Bolsove…           11754 Small To… East M… Non-co… Smaller non-coa…
##  8 E34000055 March B…           21051 Medium T… East o… Non-co… Large non-coast…
##  9 E34000056 Southam…            6567 Small To… West M… Non-co… Smaller non-coa…
## 10 E34000067 Royston…           15781 Small To… East o… Non-co… Smaller non-coa…
## # ℹ 1,094 more rows
## # ℹ 24 more variables: ttwa11cd <chr>, ttwa11nm <chr>,
## #   ttwa_classification <chr>, job_density_flag <chr>, income_flag <chr>,
## #   university_flag <chr>, level4qual_residents35_64_2011 <chr>,
## #   ks4_2012_2013_counts <dbl>,
## #   key_stage_2_attainment_school_year_2007_to_2008 <dbl>,
## #   key_stage_4_attainment_school_year_2012_to_2013 <dbl>, …

Plot data

data %>%
    
    ggplot(aes(level4qual_residents35_64_2011)) +
    geom_bar()