--- title: "Vorhofkatheter-Statistik" author: "Daniel Kraus" date: '2018-12-30' output: ioslides_presentation: default beamer_presentation: default --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = FALSE) library(tidyverse) raw_data = read_csv('vhk.csv') %>% mutate(Year = lubridate::year(Date)) cath_by_year = raw_data %>% count(Year) first_year = min(raw_data$Year) last_year = max(raw_data$Year) max_y_break = ((max(cath_by_year$n) %/% 10) + 1) * 10 ``` ## Katheterimplantationen pro Jahr ```{r cath_by_year } cath_by_year %>% ggplot(aes(x = Year, y = n)) + geom_col() + scale_y_continuous(breaks = seq(from = 0, to = max_y_break, by = 10)) + scale_x_continuous(breaks = seq(from = first_year, to = last_year, by = 1)) + labs(x = NULL, y = NULL) ``` ## Alter der Patienten ```{r patient_age} raw_data %>% ggplot(aes(group = Year, x = Year, y = Age)) + geom_boxplot() + coord_cartesian(ylim = c(20, 100)) + scale_x_continuous(breaks = seq(from = first_year, to = last_year, by = 1)) + scale_y_continuous(breaks = seq(from = 20, to = 100, by = 10)) + labs(x = NULL, y = NULL) ``` ## Geschlecht der Patienten ```{r patient_sex} raw_data %>% group_by(Year) %>% summarise(PercentFemale = sum(Sex == "weiblich") / n()) %>% ggplot(aes(x = Year, y = PercentFemale)) + geom_col() + scale_x_continuous(breaks = seq(from = first_year, to = last_year, by = 1)) + scale_y_continuous(labels = scales::percent_format(accuracy = 1)) + labs(x = NULL, y = "Anteil Frauen") ``` ## Hitparade der Implanteure ```{r greatest_surgeons} raw_data %>% count(Surgeon) %>% arrange(n) %>% top_n(10, n) %>% mutate(Surgeon = factor(Surgeon, levels = Surgeon)) %>% ggplot(aes(x = Surgeon, y = n)) + geom_col() + coord_flip() + labs(x = NULL, y = NULL) ``` ## Hitparade der Assistenten ```{r greatest_assistants} raw_data %>% count(Assistant) %>% arrange(n) %>% top_n(10, n) %>% mutate(Assistant = factor(Assistant, levels = Assistant)) %>% ggplot(aes(x = Assistant, y = n)) + geom_col() + coord_flip() + labs(x = NULL, y = NULL) ```