single_table | R Documentation |

Generates a detailed table summarizing the frequencies and counts for each level
of the specified variable, `question`

. If a grouping variable, `group_by`

, is provided,
the table extends to include row and column totals, along with additional count and
frequency columns for each level of `group_by`

(excluding specified subgroups, if any).
When survey weights are specified with `weights`

, the counts reflect the weighted values,
and a note is appended at the bottom of the table.

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

`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 |

`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 |

A gt table summarizing frequencies and counts based on the specified
parameters. If the optional `group_by`

parameter is provided, the output
will be a grouped gt table, displaying frequencies and counts for each
subgroup as well as row and column totals.

Other single-choice questions:
`single_freq()`

,
`single_summary()`

```
#Simple table
single_table(berlinbears, question = income)
#Use `group_by` to partition the question into several groups
single_table(berlinbears, question = income, group_by = gender)
#to ignore a subgroup, use `subgroups_to_exclude`
single_table(berlinbears, question = income, group_by = species,
subgroups_to_exclude = c('black bear', NA))
#Specifiy survey weights with `weights`
single_table(berlinbears, question = h_winter, group_by = gender,
weights = weights)
#to ignore NA values in the responses to `question`, set na.rm = TRUE
single_table(berlinbears, question = h_winter, na.rm = TRUE)
```

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