Sum revenue by group

Calculate total revenue by group. Total revenue is the sum price variable.

sumRevenue(df, groupVars = NULL)

Arguments

df	A data frame
groupVars	A character vector of variable names to group by

Value

A dataframe with columns for grouping variables and a column named revenue for total revenue

See also

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

Examples

# Demo data: Calculate revenue each year from fishing licenses between 2010
# and 2017
filterData(
  dataSource = "csv",
  activeFilters = list(itemType = "Fish", itemYear = c(2010, 2017))
) %>%
  sumRevenue(c("itemYear", "itemType"))
#> # A tibble: 8 x 3
#>   itemYear itemType revenue
#>   <fct>    <fct>      <dbl>
#> 1 2010     Fish      30774 
#> 2 2011     Fish      31100.
#> 3 2012     Fish      37631.
#> 4 2013     Fish      35274.
#> 5 2014     Fish      35642.
#> 6 2015     Fish      34204.
#> 7 2016     Fish      40332.
#> 8 2017     Fish      42917 
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: Calculate revenue each year from fishing licenses between 2010
# and 2017
filterData(
  dataSource = "sql",
  conn = myConn,
  activeFilters = list(itemType = "Fish", itemYear = c(2010, 2017))
) %>%
  sumRevenue(c("itemYear", "itemType"))
}