## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE,
                      comment = "#>",
                      fig.align = "center",
                      warning = FALSE,
                      screenshot.force = FALSE)

## ----message=FALSE, warning=FALSE---------------------------------------------
library(concstats)

## -----------------------------------------------------------------------------
data("creditcoops")
head(creditcoops)

## ----example-1----------------------------------------------------------------
x <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04, 0, 0)
test_firm <- concstats_firm(x) # number of firms
test_firm

## ----example-2----------------------------------------------------------------
x <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04, 0, 0)
test_share_top5 <- concstats_mstruct(x, type = "top5") # top3 market shares in %
test_share_top5

## ----example-all_mstruct------------------------------------------------------
x <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04, 0, 0)
concstats_all_mstruct(x, na.rm = TRUE, digits = 3)

## ----examples-entropy, echo=TRUE----------------------------------------------
x <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04)
test_share_entropy <- concstats_entropy(x)
test_share_entropy

# and as a non-normalized value
test_share_entropy2 <- concstats_entropy(x, normalized = FALSE)
test_share_entropy2

## ----examples-hhi, echo=TRUE--------------------------------------------------
x <- c(0.35, 0.4, 0.05, 0.1, 0.06, 0.04, 0, 0)
test_share_hhi <- concstats_hhi(x)
test_share_hhi

# a normalized value
test_share_hhi2 <- concstats_hhi(x, normalized = TRUE, digits = 3)
test_share_hhi2

# the min average of the hhi
test_share_hhi3 <- concstats_comp(x, type = "hhi_min")
test_share_hhi3

## ----examples-concstats, echo=TRUE--------------------------------------------
x<- c(0.2, 0.3, 0.5)
test_share_conc <- concstats_concstats(x, digit = 2)
test_share_conc

## -----------------------------------------------------------------------------
data("creditcoops")
head(creditcoops)

## ----visualization-prep, message=FALSE, eval=FALSE----------------------------
# library(dplyr)
# library(kableExtra)

## ----visualization-tab, echo=TRUE, eval=FALSE---------------------------------
# #data("creditcoops")
# coops_2016 <- creditcoops |>  dplyr::filter(year == 2016)
# head(coops_2016)
# 
# coops_2016 <- coops_2016[["total_loans"]] # atomic vector of total loans
# coops_2016 <- coops_2016 / sum(coops_2016)  # market shares in decimal form
# 
# # We then use the new object `coops_2016` to calculate the market structure
# # measures as a group in a one-step-procedure and capture the results in a
# # printed table:
# coops_2016_mstruct <- concstats_mstruct(coops_2016, type = "all",
#                                         digits = 2)
# coops_2016_mstruct_tab <- coops_2016_mstruct |>
#   kableExtra::kbl(caption = "Market structure 2016", digits = 2,
#                   booktabs = TRUE, align = "r") |>
#   kableExtra::kable_classic(full_width = FALSE, html_font = "Arial")
# coops_2016_mstruct_tab
# 

## ----visualization-sample-prep, echo=FALSE, eval=FALSE------------------------
# df_shares <- creditcoops |>
#   dplyr::select(coop_id, year, paired, total_loans_log)
# 

## ----echo=TRUE, eval=FALSE----------------------------------------------------
# library(ggplot2) # Data Visualizations Using the Grammar of Graphics
# 
# df_shares_plot <- df_shares |>
#   ggplot(aes(year, total_loans_log, fill = year)) +
#   geom_boxplot() +
#   geom_point() +
#   geom_line(aes(group = paired)) +
#   labs(title = "Credit cooperatives (type A)", y = "Total loans (log)",
#        caption = "Source: Andreas Schneider with data from INCOOP") +
#   theme(legend.position = "none")
# df_shares_plot