toplines

library(pollster)
library(dplyr)
library(knitr)
library(ggplot2)

The default topline table comes with columns for response category, frequency count, percent, valid percent, and cumulative percent.

topline(df = illinois, variable = voter, weight = weight) %>%
  kable()

Because the output is a tibble, it’s simple to manipulate it in any way you want after creating it. Use dplyr::select to remove columns or dplyr::filter to remove rows. For convenience, the topline function also provides ways to do this within the function call. For example, the remove argument accepts a character vector of response values to be removed from the table after all statistics are calculated. This is especially useful for survey data with a “refused” category.

topline(df = illinois, variable = voter, weight = weight, 
        remove = c("(Missing)"), pct = FALSE) %>%
  mutate(Frequency = prettyNum(Frequency, big.mark = ",")) %>%
  kable(digits = 0)

Refer to the kableExtra package for lots of examples on how to format the appearance of these tables in either HTML or PDF latex formats. I recommend the vignettes “Create Awesome HTML Table with knitr::kable and kableExtra” and "Create Awesome PDF Table with knitr::kable and kableExtra.

topline(df = illinois, variable = voter, weight = weight) %>%
  ggplot(aes(Response, Percent, fill = Response)) +
  geom_bar(stat = "identity")

moe_topline(df = illinois, variable = educ6, weight = weight)
#> # A tibble: 6 x 6
#>   Response Frequency Percent `Valid Percent`   MOE `Cumulative Percent`
#>   <fct>        <dbl>   <dbl>           <dbl> <dbl>                <dbl>
#> 1 LT HS    10770999.   10.5            10.5  0.326                 10.5
#> 2 HS       31409418.   30.6            30.6  0.490                 41.1
#> 3 Some Col 21745113.   21.2            21.2  0.435                 62.3
#> 4 AA        8249909.    8.03            8.03 0.289                 70.3
#> 5 BA       19937965.   19.4            19.4  0.421                 89.7
#> 6 Post-BA  10565110.   10.3            10.3  0.323                100