This week is Modes Less Traveled - Bicycling and Walking to Work in the United States: 2008-2012 from the ACS.
The commute.csv dataset on Github was tidied from 6 raw excel files. The code and final dataset was already provided.
Code for tidying summary tables by demographics was also provided.
First, look at data using head:
## # A tibble: 6 x 9
## city state city_size mode n percent moe state_abb state_region
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr> <chr>
## 1 Aberdeen … South D… Small Bike 110 0.8 0.5 SD North Centr…
## 2 Acworth c… Georgia Small Bike 0 0 0.4 GA South
## 3 Addison v… Illinois Small Bike 43 0.2 0.3 IL North Centr…
## 4 Adelanto … Califor… Small Bike 0 0 0.5 CA West
## 5 Adrian ci… Michigan Small Bike 121 1.5 1 MI North Centr…
## 6 Agawam To… Massach… Small Bike 0 0 0.2 MA NortheastStill some small things to tidy:
- fix those with missing state abbreviation or region
- re-check to see the errors are all fixed
## # A tibble: 4 x 9
## city state city_size mode n percent moe state_abb state_region
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr> <chr>
## 1 El Paso de… Ca Small Bike 71 0.5 0.4 <NA> <NA>
## 2 West Sprin… Massac… Small Bike 23 0.2 0.2 <NA> <NA>
## 3 Washington… Distri… Large Bike 9347 3.1 0.2 <NA> <NA>
## 4 Washington… Distri… Large Walk 37055 12.1 0.5 <NA> <NA>## # A tibble: 2 x 9
## city state city_size mode n percent moe state_abb state_region
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr> <chr>
## 1 El Paso de … Ca Small Bike 71 0.5 0.4 CA West
## 2 West Spring… Massa… Small Bike 23 0.2 0.2 MA Northeast## # A tibble: 0 x 9
## # … with 9 variables: city <chr>, state <chr>, city_size <chr>, mode <chr>,
## # n <dbl>, percent <dbl>, moe <dbl>, state_abb <chr>, state_region <chr>Next, I clean the added words “village”, “town”, “city”, etc from the end of each city name, create a concatenation of city and state, and geocode using google maps. I saved this as a CSV to save time when re-running the file. The code is commented out, but shown for completeness.
I used choroplethrMaps to get the USA state-level data, which I joined to state averages of walk and bike travel.
Below are box plots of mode of travel by city size and region. There are more walkers, more variation in small cities, and it looks like the northeast may have more walkers than other regions.
Finally, I map the data below. Each point represents a city in the dataset. The points and states are colored according to the percent of mode of travel, by city or averaged over the whole state. I also piped to plotly so the maps are interactive.
