Data Analytics and Computational Social Science: Homework 2

Damion Perry

The following is data summarizing the US Railroad employment numbers from 2012.

‘state’

type -> character string Represents the state that railroad employees worked.

‘county’

type -> character string Represents the county within the corresponding state.

‘num_employees’

type -> dbl Number of employees working for the railroad in the corresponding state and county.

Tidy & Wrangle

The original dataset has been modified to display the results for US railroad employment in Massachusetts.

library(readxl)
StateCounty2012 <- read_excel("HW2/StateCounty2012.xlsx", skip = 2)
state_county <- StateCounty2012[c(1,3,5)]
state_county %>% 
  rename(state = STATE, county = COUNTY, num_employees = TOTAL) %>%
  drop_na(county) %>% 
  filter(state == "MA") %>% 
  arrange(desc(num_employees))

# A tibble: 12 × 3
   state county     num_employees
   <chr> <chr>              <dbl>
 1 MA    MIDDLESEX            673
 2 MA    SUFFOLK              558
 3 MA    PLYMOUTH             429
 4 MA    NORFOLK              386
 5 MA    ESSEX                314
 6 MA    WORCESTER            310
 7 MA    BRISTOL              232
 8 MA    HAMPDEN              202
 9 MA    FRANKLIN             113
10 MA    HAMPSHIRE             68
11 MA    BERKSHIRE             50
12 MA    BARNSTABLE            44

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Citation

For attribution, please cite this work as

Perry (2022, Feb. 9). Data Analytics and Computational Social Science: Homework 2. Retrieved from https://github.com/DACSS/dacss_course_website/posts/httpsdamionperrygithubiodcss601posts/

BibTeX citation

@misc{perry2022homework,
  author = {Perry, Damion},
  title = {Data Analytics and Computational Social Science: Homework 2},
  url = {https://github.com/DACSS/dacss_course_website/posts/httpsdamionperrygithubiodcss601posts/},
  year = {2022}
}