Filter the health data

Description

The ‘data4health’ package provides a function for filtering dataframes. It allows users to filter data based on various conditions and column types.

d4h_filter(data, ...)

Arguments

  • data: The dataframe to be filtered.

  • ...: Any columns that you want to be filtered. Each columns should be passed with a list including the filter condition and the filter values. Filter conditions depend on the column type:

    • numeric = “over”, “under”, “between”, “equal”
    • Date = “after”, “before”, “during”,
    • character = “include”, “exclude”, “match”, “starts”, “ends”

Returns

A filtered dataframe.

Examples

## View the first rows
head(example_dataset)

# filter numeric variable (CODE_GEO greater than 100050)
filtered_numeric <- d4h_filter(
  example_dataset,
  CODE_GEO = list(over = 100050)
)

# filter Date variable (cases after Jan 1, 2024)
filtered_date_after <- d4h_filter(
  example_dataset,
  DATE_INI = list(after = as.Date("2024-01-01"))
)

# filter Date variable between two dates
filtered_date_between <- d4h_filter(
  example_dataset,
  DATE_INI = list(
    between = as.Date(c("2023-06-01", "2023-12-31"))
  )
)

# filter character variable (include only Positive results)
filtered_positive <- d4h_filter(
  example_dataset,
  RESULT_LABORATORY = list(include = "Positive")
)

# exclude specific geographic areas
filtered_exclude_geo <- d4h_filter(
  example_dataset,
  NAME_GEO = list(exclude = c("Agrabah", "Atlantica"))
)

# combine multiple filters
filtered_combined <- d4h_filter(
  example_dataset,
  RESULT_LABORATORY = list(include = "Positive"),
  HOSPITALISED = list(include = "S"),
  DATE_INI = list(after = as.Date("2024-01-01"))
)