trendtestR (version 1.0.1)

filter_by_groupcol: Filter and optionally reshape a data frame by group column / Nach Gruppenspalte filtern und optional umstrukturieren

Description

This function filters a data frame based on specified grouping levels and optionally transforms it into a wide format for further analysis. It supports retaining extra columns and provides robust error checking.

Usage

filter_by_groupcol(
  df,
  group_col,
  value_col,
  datum_col,
  keep_levels = NULL,
  to_wide = FALSE,
  keep_other_cols = FALSE
)

Value

A filtered and optionally reshaped tibble.

Arguments

df

A data.frame or tibble containing the data.

group_col

A string specifying the grouping column (e.g., "region", "age_group").

value_col

A string for the value column (default: "neue_faelle").

datum_col

A string for the date column (default: "datum").

keep_levels

Optional vector of levels to retain in group_col. Default = NULL (keep all).

to_wide

Logical, if TRUE returns a wide-format table (each level a column).

keep_other_cols

Logical, if TRUE keeps all other original columns.

Details

Diese Funktion filtert einen Data Frame basierend auf bestimmten Gruppenwerten und kann ihn optional in ein Wide-Format umwandeln. Es koennen weitere Spalten beibehalten werden, und die Funktion enthaelt robuste Fehlerpruefungen.

This function is particularly useful for preparing time series grouped by categories, such as cases per region or age group.

Diese Funktion eignet sich besonders zur Vorbereitung gruppierter Zeitreihen, z.B. nach Region oder Altersgruppe.

Examples

# English / Deutsch
df <- data.frame(
  datum = as.Date("2024-01-01") + 0:9,
  gruppe = rep(c("A", "B"), each = 5),
  neue_faelle = c(10, 12, 13, 15, 11, 20, 21, 22, 19, 18),
  region = rep("Berlin", 10)
)

filter_by_groupcol(
  df,
  group_col = "gruppe",
  value_col = "neue_faelle",
  datum_col = "datum",
  keep_levels = "A"
)

filter_by_groupcol(
  df,
  group_col = "gruppe",
  value_col = "neue_faelle",
  datum_col = "datum",
  to_wide = TRUE
)