single_freq {surveyexplorer}

Plot frequencies of responses for a single-choice question.

Description

generates a bar chart of class ggplot illustrating how responses are distributed for a specific single-choice question. If you provide a grouping variable using group_by the chart includes facets for each subgroup. Additionally, if you specify survey weights with weights the chart reflects weighted response frequencies.

Usage

single_freq(
  dataset,
  question,
  group_by = NULL,
  subgroups_to_exclude = NULL,
  weights = NULL,
  na.rm = FALSE
)

Arguments

dataset

The input dataframe (or tibble) of survey questions

question

The categorical variable of interest for which frequencies and counts will be calculated, can be selected by using tidyselect semantics

group_by

Optional variable to group the analysis. If provided, the frequencies and counts will be calculated within each subgroup.

subgroups_to_exclude

Optional vector specifying subgroups to exclude from the analysis.

weights

Optional variable containing survey weights. If provided, frequencies and counts will be weighted accordingly.

na.rm

Logical indicating whether to remove NA values from question before analysis.

Value

A ggplot2 object with a bar chart displaying response frequencies. If "group_by" is provided, facets show subgroup details. If "weights" are specified, the chart displays weighted frequencies.

See Also

Other single-choice questions: single_summary(), single_table()

Examples

#Simple barchart
single_freq(berlinbears, question = income)

#Use `group_by` to facet the graph into several groups
single_freq(berlinbears, question = income, group_by = gender)

#to ignore a subgroup, use `subgroups_to_exclude`
single_freq(berlinbears, question = income, group_by = species,
subgroups_to_exclude = c('black bear', NA))

#Specify survey weights with `weights`
single_freq(berlinbears, question = h_winter, group_by = gender, weights = weights)

#to ignore NA values in the responses to `question`, set na.rm = TRUE
single_freq(berlinbears, question = h_winter, na.rm = TRUE)