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Prep data for rohani plots. Prep steps include creating additional time unit fields, summarizing the series variable by time unit and grouping variable (the x and y axis variables) ,and optionally normalizing series data to be in the range (0,1). By default, the grouping variable is ranked in order of the summarized series variable. Needs to be generalized more, might need to handle the case where the desired y-axis is a second time unit, as in the seasonal heatmap plot and therefore making use of the year_end_fix function.

Usage

iidda_prep_rohani(
  data,
  series_variable = NULL,
  time_variable = "period_end_date",
  start_time_variable = "period_start_date",
  time_unit = "year",
  grouping_variable = "cause",
  ranking_variable = NULL,
  normalize = FALSE,
  handle_missing_values = HandleMissingValues(na_remove = FALSE, na_replace = NULL),
  handle_zero_values = HandleZeroValues(zero_remove = FALSE, zero_replace = NULL),
  create_nonexistent = FALSE
)

Arguments

data

data frame containing time series data

series_variable

column name of series variable in data, default is "deaths"

time_variable

column name of time variable in data, default is "period_end_date"

start_time_variable

column name of time variable in data, default is "period_end_date"

time_unit

a vector of new time unit fields to create from start_time_variable and end_time_variable. Defaults to "c("year")". The currently functionality expects that "year" is included, should be made more general to incorporate any of iidda.analysis:::time_units.

grouping_variable

column name of grouping variable to appear on the y-axis of the heatmap.

ranking_variable

column name of variable used to rank the grouping variable.

normalize

boolean flag to normalize series_variable data to be between 0 and 1.

handle_missing_values

function to handle missing values, defaults to HandleMissingValues

handle_zero_values

function to handle zero values, defaults to HandleZeroValues

create_nonexistent

boolean flag to create NA records for non-existent time_unit and grouping_variable. This creates all combinations of time_unit and grouping_variable to ensure there are no missing records.

Value

all fields indata with records prepped for plotting rohani heatmaps. The name of the new time_unit fields will be named from lubridate_funcs.