## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----intro, eval = FALSE------------------------------------------------------
# library(ExPanDaR)
# library(gapminder)
#
# ExPanD(df = gapminder, cs_id = "country", ts_id = "year")
## ----omit_components, eval = FALSE--------------------------------------------
# library(ExPanDaR)
# library(gapminder)
# data(gapminder)
#
# ExPanD(df = gapminder, cs_id = "country", ts_id = "year",
# components = c(sample_selection = FALSE, missing_values = FALSE))
## ----select_components, eval = FALSE------------------------------------------
# library(ExPanDaR)
# library(gapminder)
# data(gapminder)
#
# ExPanD(df = gapminder, cs_id = "country", ts_id = "year",
# components = c(descriptive_table = TRUE,
# by_group_violin_graph = TRUE,
# scatter_plot = TRUE,
# regression = TRUE))
## ----include_intro, eval = FALSE----------------------------------------------
# library(ExPanDaR)
# library(gapminder)
# data(gapminder)
#
# ExPanD(df = gapminder, cs_id = "country", ts_id = "year",
# title = "Explore the Preston Curve",
# abstract = paste("This interactive display uses 'gapminder' data to",
# "let you explore the Preston Curve. Scroll down and enjoy!"),
# components = c(descriptive_table = TRUE,
# by_group_violin_graph = TRUE,
# scatter_plot = TRUE,
# regression = TRUE))
## ----include_df_def, eval = FALSE---------------------------------------------
# library(ExPanDaR)
# library(gapminder)
# data(gapminder)
#
# df_def <- data.frame(
# var_name = names(gapminder),
# var_def = c("Name of the country",
# "Continent where country is located",
# "Year of data",
# "Life expectancy in years at birth",
# "Population in million",
# "Gross Domestic Product (GDP) per capita"),
# type = c("cs_id", "factor", "ts_id", rep("numeric", 3))
# )
#
# gapminder$pop <- gapminder$pop / 1e6
#
# ExPanD(df = gapminder,
# title = "Explore the Preston Curve",
# abstract = paste("This interactive display uses 'gapminder' data to",
# "let you explore the Preston Curve. Scroll down and enjoy!"),
# components = c(descriptive_table = TRUE,
# by_group_violin_graph = TRUE,
# quantile_trend_graph = TRUE,
# scatter_plot = TRUE,
# regression = TRUE),
# df_def = df_def)
## ----include_dl_clist, eval = FALSE-------------------------------------------
# library(ExPanDaR)
# library(gapminder)
# data(gapminder)
#
# df_def <- data.frame(
# var_name = names(gapminder),
# var_def = c("Name of the country",
# "Continent where country is located",
# "Year of data",
# "Life expectancy in years at birth",
# "Population in million",
# "Gross Domestic Product (GDP) per capita"),
# type = c("cs_id", "factor", "ts_id", rep("numeric", 3))
# )
#
# gapminder$pop <- gapminder$pop / 1e6
#
# clist <- readRDS("my_config.RDS")
#
# ExPanD(df = gapminder,
# title = "Explore the Preston Curve",
# abstract = paste("This interactive display uses 'gapminder' data to",
# "let you explore the Preston Curve. Scroll down and enjoy!"),
# components = c(descriptive_table = TRUE,
# by_group_violin_graph = TRUE,
# scatter_plot = TRUE,
# regression = TRUE),
# df_def = df_def,
# config_list = clist)
## ----include_manual_clist, eval = FALSE---------------------------------------
# library(ExPanDaR)
# library(gapminder)
# data(gapminder)
#
# df_def <- data.frame(
# var_name = names(gapminder),
# var_def = c("Name of the country",
# "Continent where country is located",
# "Year of data",
# "Life expectancy at birth, in years",
# "Population in million",
# "Gross Domestic Product (GDP) per capita in US-$, inflation-adjusted"),
# type = c("cs_id", "factor", "ts_id", rep("numeric", 3)),
# stringsAsFactors = FALSE
# )
#
# gapminder$pop <- gapminder$pop / 1e6
#
# clist <- list(
# scatter_x = "gdpPercap",
# scatter_y = "lifeExp",
# scatter_size = "pop",
# scatter_color = "continent",
# scatter_loess = TRUE,
# scatter_sample = FALSE,
#
# reg_y = "lifeExp",
# reg_x = "gdpPercap",
# reg_fe1 = "country",
# reg_fe2 = "year",
# cluster = "4" # Now this is hard to guess
# # 1: none, 2: first FE, 3: second FE, 4: both FE
# )
#
# ExPanD(df = gapminder,
# title = "Explore the Preston Curve",
# abstract = paste("This interactive display uses 'gapminder' data to",
# "let you explore the Preston Curve. Scroll down and enjoy!"),
# components = c(descriptive_table = TRUE,
# by_group_violin_graph = TRUE,
# scatter_plot = TRUE,
# regression = TRUE),
# df_def = df_def,
# config_list = clist)
## ----include_udvs, eval = FALSE-----------------------------------------------
# library(ExPanDaR)
# library(gapminder)
# data(gapminder)
#
# df_def <- data.frame(
# var_name = names(gapminder),
# var_def = c("Name of the country",
# "Continent where country is located",
# "Year of data",
# "Life expectancy in years at birth",
# "Population in million",
# "Gross Domestic Product (GDP) per capita"),
# type = c("cs_id", "factor", "ts_id", rep("numeric", 3)),
# stringsAsFactors = FALSE
# )
#
# gapminder$pop <- gapminder$pop / 1e6
#
# clist <- list(
# scatter_x = "gdpPercap",
# scatter_y = "lifeExp",
# scatter_size = "pop",
# scatter_color = "continent",
# scatter_loess = TRUE,
# scatter_sample = FALSE,
#
# reg_y = "lifeExp",
# reg_x = "gdpPercap",
# reg_fe1 = "country",
# reg_fe2 = "year",
# cluster = "4" # No this is hard to guess 1: none, 2: first FE, 3: second FE, 4: both FE
# )
#
# ExPanD(df = gapminder,
# title = "Explore the Preston Curve",
# abstract = paste("This interactive display uses 'gapminder' data to",
# "let you explore the Preston Curve. Scroll down and enjoy!"),
# components = c(descriptive_table = TRUE,
# by_group_violin_graph = TRUE,
# scatter_plot = TRUE,
# udvars = TRUE,
# regression = TRUE),
# df_def = df_def,
# config_list = clist)
## ----include_html, eval = FALSE-----------------------------------------------
# library(ExPanDaR)
# library(gapminder)
# data(gapminder)
#
# df_def <- data.frame(
# var_name = names(gapminder),
# var_def = c("Name of the country",
# "Continent where country is located",
# "Year of data",
# "Life expectancy in years at birth",
# "Population in million",
# "Gross Domestic Product (GDP) per capita"),
# type = c("cs_id", "factor", "ts_id", rep("numeric", 3)),
# stringsAsFactors = FALSE
# )
#
# gapminder$pop <- gapminder$pop / 1e6
#
# clist <- list(
# scatter_x = "gdpPercap",
# scatter_y = "lifeExp",
# scatter_size = "pop",
# scatter_color = "continent",
# scatter_loess = TRUE,
# scatter_sample = FALSE,
#
# reg_y = "lifeExp",
# reg_x = "gdpPercap",
# reg_fe1 = "country",
# reg_fe2 = "year",
# cluster = "4" # No this is hard to guess 1: none, 2: first FE, 3: second FE, 4: both FE
# )
#
# html_blocks <- c(
# paste('<div class="col-sm-2"><h3>Variation of life expectancy',
# "across regions and income levels</h3></div>",
# '<div class="col-sm-10">',
# "<p> </p>As you see below, life expectancy varies widely",
# "across countries and continents. One potential reason for this",
# "variation is the difference in income levels across countries.",
# "This association is visualized by the",
# "<a href=https://en.wikipedia.org/wiki/Preston_curve>",
# "Preston Curve</a> that you also find below.",
# "</div>"),
# paste('<div class="col-sm-2"><h3>Transform variables</h3></div>',
# '<div class="col-sm-10">',
# "The Preston Curve is far from",
# "linear. Maybe you can come up with a transformation",
# "of GDP per capita that makes the association",
# "a little bit more well behaved?",
# "Use the dialog below to define a transformed",
# "measure of GDP per capita and assess its association",
# "with life expectancy in the scatter plot above.",
# "</div>"),
# paste('<div class="col-sm-2"><h3>Assess Robustness</h3></div>',
# '<div class="col-sm-10">',
# "You see below that the linear regression coefficient",
# "for GDP per capita is <i>negative</i>",
# "and signficant in a panel model with country and year",
# "fixed effects.",
# "Does this also hold when you use a log-transformed version",
# "of GDP per capita?",
# "</div>")
# )
#
# ExPanD(df = gapminder,
# title = "Explore the Preston Curve",
# abstract = paste("This interactive display uses 'gapminder' data to",
# "let you explore the Preston Curve. Scroll down and enjoy!"),
# components = c(descriptive_table = TRUE,
# html_block = TRUE,
# by_group_violin_graph = TRUE,
# scatter_plot = TRUE,
# html_block = TRUE,
# udvars = TRUE,
# html_block = TRUE,
# regression = TRUE),
# df_def = df_def,
# config_list = clist,
# html_blocks = html_blocks)