Railroad Employment data

Reading in the railroad dataset

library(readxl)
  library(dplyr)
  State_county <- read_excel("../../_data/StateCounty2012.xls", skip=3)
  

The data has been read in. Let’s see how it looks like -

head(State_county)

# A tibble: 6 × 5
  STATE     ...2  COUNTY               ...4  TOTAL
  <chr>     <lgl> <chr>                <lgl> <dbl>
1 AE        NA    APO                  NA        2
2 AE Total1 NA    <NA>                 NA        2
3 AK        NA    ANCHORAGE            NA        7
4 AK        NA    FAIRBANKS NORTH STAR NA        2
5 AK        NA    JUNEAU               NA        3
6 AK        NA    MATANUSKA-SUSITNA    NA        2

tail(State_county)

# A tibble: 6 × 5
  STATE                                       ...2  COUNTY ...4  TOTAL
  <chr>                                       <lgl> <chr>  <lgl> <dbl>
1 <NA>                                        NA    <NA>   NA       NA
2 CANADA                                      NA    <NA>   NA      662
3 <NA>                                        NA    <NA>   NA       NA
4 1  Military designation.                    NA    <NA>   NA       NA
5 <NA>                                        NA    <NA>   NA       NA
6 NOTE:  Excludes 2,896 employees without an… NA    <NA>   NA       NA

This needs further cleaning to make it suitable for further analysis.

State_county <- select(State_county, -c(2, 4))
State_county <- State_county[complete.cases(State_county),]
head(State_county)

# A tibble: 6 × 3
  STATE COUNTY               TOTAL
  <chr> <chr>                <dbl>
1 AE    APO                      2
2 AK    ANCHORAGE                7
3 AK    FAIRBANKS NORTH STAR     2
4 AK    JUNEAU                   3
5 AK    MATANUSKA-SUSITNA        2
6 AK    SITKA                    1

tail(State_county)

# A tibble: 6 × 3
  STATE COUNTY     TOTAL
  <chr> <chr>      <dbl>
1 WY    SHERIDAN     252
2 WY    SUBLETTE       3
3 WY    SWEETWATER   196
4 WY    UINTA         49
5 WY    WASHAKIE      10
6 WY    WESTON        37

This looks much better!