library(magrittr) library(dplyr) library(maps) library(graphics) source('../R/make_filename.R') source('../R/fars_read_years.R') source('../R/fars_summerize_years.R') source('../R/fars_map_state.R') # source('../data') # source('../Data/accident_2014.csv.bz2') # source('../Data/accident_2015.csv.bz2')
The function fars_read()
takes as argument the name of a file and reads it into R. if the function does not exist it will return an error: "The file does not exist".
data_2013 <- fars_read('accident_2013.csv.bz2')
One way to use this function is to enter the file name manually. However since we use specific files with generic format "accident_YYYY.csv.bz2". All we need to do is to replace the YYYY with a four digit year. This can be done with the function make_filename()
and passing the four-digit year as argument.
filename = make_filename(2013) print(filename)
Instead of reading files one by one you can use the function fars_read_years()
and passing in a vector of years. Then the function will return a list of the table where each element contains the data from a file.
tbl <- fars_read_years(c(2013, 2014, 2015))
the function fars_summerize_years()
takes a vector of years and calls fars_read_years()
with the vector of years. it does a row binding over all the tbls it groups the yielded tibble by year and MONTH and then counts the occurances and then it makes a wide tibble from the long tibble according to year.
summary_tbl <- fars_summerize_years(c(2013, 2014, 2015)) print(summary_tbl)
By calling this function you can get the map of accidents in a year and a state in US. You can get this map by inputing a state number and a year.
fars_map_state(10, 2013)
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