enum_by_year.R

DESCRIPTION <- "build a table of year by some enumeration in the data. Extremely useful for stream, stacked bar, and line charts."

load(data)

# motive by year (2009-2014) for Breaches
## TO USE: 0. Change the filters in the first line unless you want no Error actions, only Breaches, and no other filters
##         1. Change the starts_with()'s in the first select statement to the columns you want
##         2. Change the "4" in the separate line to the number of columns. (if you're doing actor.Internal.motive.m, it'd be 4 because there's 4 parts.)
##         3. Change the "4" in the select line below the separate line to whatever number you used in step 2.
##         4. Change the "4" in the rename line to whatever number you used in step 2.
## NOTE 1: This only works if all enumerations are the same level down the tree.  (ie no actor.Internal.motive.m joined with actor.unknown)
## NOTE 2: If you remove the separate-select-rename lines you don't join the lower level values
temp <- vz %>% 
  filter(attribute.confidentiality.data_disclosure.Yes, action.Error != TRUE) %>%    # Filter to the data we want to work on.
  select(starts_with("actor.Internal.motive"), 
         starts_with("actor.External.motive"), 
         starts_with("actor.Partner.motive"), 
         timeline.incident.year) %>%   # Select only the data column(s) we plan to count & the year we plan to count by
  gather(enum, 
         value, 
         -timeline.incident.year) %>%  # Gather column name - value pairs into 2 columns: enum - value
  filter(value) %>%  # Remove the the rows that are false (ie where the enumeration wasn't true and, tehrefore, which we don't want to count)
  select(-value) %>%  # Remove the value column as we no longer need it
  separate(enum, 1:4, "[.]", extra="merge") %>%  # separate the sections of the VERIS enumeration
  select(timeline.incident.year, `4`) %>%  # Remove the other columns generated by splitting VERIS enumerations
  rename(enum = `4`) %>%  # Rename the last column back to "enum" (which it was before)
  group_by(timeline.incident.year, enum) %>%  # group the data by year and enumeration (the cells in the ultimate table)
  summarize(x = n()) %>%  # Each cell's value is the count of the number of times the enum - year combination is true.  n() counts the rows in the group.
  mutate(n = sum(x)) %>%  # Sum the x values to get an n.  I don't know why, but this does it by the first group_by grouping (in this case 'year') 
  mutate(freq = round(100 * x/n, 2), `count/total` = paste(x, n, sep="/"))  # Create frequency and count/total columns from x and n
temp %>% acast(enum~timeline.incident.year, value.var="count/total")  # turn the enum, year, count/total columns into a table with columns of year, rows of enum, and values of count/total
temp %>% acast(enum~timeline.incident.year, value.var="freq", fill=0)  # turn the enum, year, freq columns into a table with columns of year, rows of enum, and values of freq