Count customers by permit groups

Count customers who bought each combination of permits and stamps

itemGroupCount(df)

Arguments

df	A data frame

See also

Other analysis functions: calcChurn, calcGenderProportion, calcParticipation, calcRecruitment, countCustomers, countItems, sumRevenue

Examples

# Demo data: Count number of customers by combination of items purchased
filterData(
  dataSource = "csv",
  activeFilters = list(
    itemType = c("Fish", "Deer", "Spring Turkey"),
    itemYear = c(2018, 2018)
  )
) %>%
  itemGroupCount()
#> # A tibble: 21 x 5
#>    groupID customers itemType      purchase degree
#>      <int>     <int> <chr>            <dbl>  <dbl>
#>  1       1      1466 Deer                 0      1
#>  2       1      1466 Fish                 1      1
#>  3       1      1466 Spring Turkey        0      1
#>  4       2       770 Deer                 1      1
#>  5       2       770 Fish                 0      1
#>  6       2       770 Spring Turkey        0      1
#>  7       3       164 Deer                 1      2
#>  8       3       164 Fish                 1      2
#>  9       3       164 Spring Turkey        0      2
#> 10       4       130 Deer                 0      1
#> # … with 11 more rows
if (FALSE) {
# Database connection. Suggest using keyring package to avoid hardcoding
# passwords
myConn <- DBI::dbConnect(odbc::odbc(),
  dsn = "HuntFishApp", # Your datasource name
  uid = keyring::key_get("HuntFishAppUID"), # Your username
  pwd = keyring::key_get("HuntFishAppPWD")
) # Your password

# SQL Backend: Count number of customers by combination of items purchased
filterData(
  dataSource = "sql",
  conn = myConn,
  activeFilters = list(
    itemType = c("Fish", "Deer", "Spring Turkey"),
    itemYear = c(2018, 2018)
  )
) %>%
  itemGroupCount()
}