## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 8,
  fig.height = 5
)
has_ggalluvial <- requireNamespace("ggalluvial", quietly = TRUE)
has_treemapify <- requireNamespace("treemapify", quietly = TRUE)
has_maps       <- requireNamespace("maps", quietly = TRUE)
has_ggfittext  <- requireNamespace("ggfittext", quietly = TRUE)
has_ggupset    <- requireNamespace("ggupset", quietly = TRUE)

## ----setup--------------------------------------------------------------------
library(litReview)
data(studies)
head(studies)

## ----bar-design---------------------------------------------------------------
reviewBar(studies, Design)

## ----bar-custom---------------------------------------------------------------
library(ggplot2)
reviewBar(studies, Design, fill = "#59a14f") +
  labs(title = "Study Designs", subtitle = "n = 12 studies")

## ----bar-studlabs, fig.height = 6, eval = has_ggfittext-----------------------
reviewBar(studies, Design, fill = PALETTE[2], studlabs = TRUE)

## ----bar-outcome, fig.height=3------------------------------------------------
reviewBar(studies, Outcome, fill = PALETTE[4], width = 0.6)

## ----bar-labelspace, fig.height=9---------------------------------------------
reviewBar(studies, Country, fill = PALETTE[6], label_space = 2)

## ----stacked-fill, fig.height = 5---------------------------------------------
reviewStackedBar(studies, Design, RiskOfBias)

## ----stacked-count, fig.height = 5--------------------------------------------
reviewStackedBar(studies, Design, RiskOfBias, position = "stack")

## ----waffle-outcome, fig.height = 4-------------------------------------------
reviewWaffle(studies, Outcome, ncol = 11)

## ----pie-design---------------------------------------------------------------
reviewPie(studies, Design)

## ----pie-full-----------------------------------------------------------------
reviewPie(studies, Design, donut = FALSE)

## ----overlap, fig.height = 4--------------------------------------------------
reviewOverlap(studies, Design, Outcome, fill = PALETTE[3])

## ----upset, fig.height = 5, eval = has_ggupset, warning = FALSE---------------
reviewUpset(studies, Outcome)

## ----upset-degree, fig.height = 5, eval = has_ggupset, warning = FALSE--------
reviewUpset(studies, Intervention, sort_by = "degree", n_intersections = 10)

## ----alluvial, fig.height = 5, eval = has_ggalluvial--------------------------
reviewAlluvial(studies, c("Design", "Outcome"))

## ----alluvial-prop, fig.height = 5, eval = has_ggalluvial---------------------
reviewAlluvial(studies, c("Design", "Outcome"), labels = "prop")

## ----alluvial-flow, fig.height = 5, eval = has_ggalluvial---------------------
reviewAlluvial(studies, c("Design", "Outcome"), labels = "none",
               flow_labels = TRUE)

## ----alluvial-labels, fig.height = 5, eval = has_ggalluvial-------------------
reviewAlluvial(studies, c("Design", "Outcome","AgeGroup"),
               axis_labels = c("Study Design", "Reported Outcome", "Age group"))

## ----treemap, fig.height = 4, eval = has_treemapify---------------------------
reviewTreemap(studies, Design)

## ----treemap-color, fig.height = 5, eval = has_treemapify---------------------
reviewTreemap(studies, Intervention, color_by = InterventionType)

## ----treemap-studlabs, fig.height = 5, eval = has_treemapify------------------
reviewTreemap(studies, Design, studlabs = TRUE)

## ----trend--------------------------------------------------------------------
reviewTrend(studies, Design)

## ----trend-count--------------------------------------------------------------
reviewTrend(studies, Design, labels = "count")

## ----trend-percent------------------------------------------------------------
reviewTrend(studies, Design, labels = "percent")

## ----trend-both---------------------------------------------------------------
reviewTrend(studies, Design, labels = "both")

## ----trend-studies------------------------------------------------------------
reviewTrend(studies, Design, labels = "studies")

## ----map, fig.width = 10, fig.height = 5, eval = has_maps---------------------
reviewMap(studies)

## ----table-design-------------------------------------------------------------
reviewTable(studies, Design)

## ----na-data------------------------------------------------------------------
df_na <- data.frame(
  StudyID = paste0("S", 1:10),
  Design  = c("RCT", "Cohort", NA, "RCT", "Case-control",
              NA, "RCT", "Cohort", NA, "RCT"),
  stringsAsFactors = FALSE
)

## ----na-default---------------------------------------------------------------
summarize_data(df_na, Design)

## ----na-pct-reported----------------------------------------------------------
summarize_data(df_na, Design, na_in_percent = FALSE)

## ----na-keep------------------------------------------------------------------
summarize_data(df_na, Design, na.rm = FALSE)

## ----na-custom----------------------------------------------------------------
summarize_data(df_na, Design, na.rm = FALSE, na_label = "Missing",
               na_in_percent = FALSE)

## ----na-bar, fig.height = 4---------------------------------------------------
reviewBar(df_na, Design, na.rm = FALSE, na_label = "Missing", na_in_percent = FALSE)

## ----na-pie-------------------------------------------------------------------
reviewPie(df_na, Design, na.rm = FALSE)

## ----custom-id----------------------------------------------------------------
df <- data.frame(
  ID = paste0("A", 1:5),
  Type = c("X", "Y", "X", "Z", "X"),
  stringsAsFactors = FALSE
)
reviewBar(df, Type, study_id = ID)

## ----summarize----------------------------------------------------------------
summarize_data(studies, Design)

## ----palette------------------------------------------------------------------
PALETTE