## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 7,
  fig.height = 4
)

## ----setup--------------------------------------------------------------------
library(ezrsurvey)

## -----------------------------------------------------------------------------
podracing_survey[, c("respondent_id", "demo_gender", "demo_age", "nps_value")]

## -----------------------------------------------------------------------------
calc_percentage(podracing_survey, demo_gender, sort = "desc")

## -----------------------------------------------------------------------------
calc_percentage(podracing_survey, satis_return, by = region, wide = TRUE)

## -----------------------------------------------------------------------------
calc_percentage_multi(podracing_survey, "motivations_",
                      id = respondent_id, sort = "desc")

## -----------------------------------------------------------------------------
packed <- data.frame(
  respondent = 1:4,
  motivations = c("Speed; Drivers", "Speed", "", "Betting; Speed")
)

calc_percentage_multi(packed, "motivations", id = respondent, sort = "desc")

## -----------------------------------------------------------------------------
split_multi(packed, motivations)

## -----------------------------------------------------------------------------
register_order(
  "education",
  levels = c("Primary or less", "Lower secondary", "Upper secondary",
             "Short-cycle tertiary", "Bachelor or equivalent",
             "Master or equivalent", "Doctoral or equivalent"),
  vars = "demo_edu"
)

calc_percentage(podracing_survey, demo_edu)

## -----------------------------------------------------------------------------
calc_nps(podracing_survey, nps_value)

## -----------------------------------------------------------------------------
plot_nps(podracing_survey, nps_value)

## -----------------------------------------------------------------------------
model <- ipm_model(podracing_survey, nps_value, "ratings_")
model

## -----------------------------------------------------------------------------
previous <- transform(model, performance = performance - c(.3, -.1, .2, 0, .1))
compare_values(model, previous) %>%
  plot_diff()

## -----------------------------------------------------------------------------
diagnose(podracing_survey, demo_gender, nps_value)

## -----------------------------------------------------------------------------
precision_summary(podracing_survey)

## ----eval = FALSE-------------------------------------------------------------
# calc_percentage(podracing_survey, demo_gender) %>% save_data("gender.xlsx")
# plot_nps(podracing_survey, nps_value) %>% save_plot("nps.png")
# 
# # several tables, one tab each
# export_xlsx(
#   gender = calc_percentage(podracing_survey, demo_gender),
#   job    = calc_percentage(podracing_survey, demo_job),
#   path   = "summary.xlsx"
# )

## ----include = FALSE----------------------------------------------------------
remove_order("education")