Finish statistics for 2018.

columns.tex

@@ -0,0 +1,38 @@
+% From: https://support.rstudio.com/hc/en-us/community/posts/202717656-Can-we-have-columns-in-rmarkdown-beamer-presentations-
+% 
+% In the YAML header of your Rmd file, add a reference to a tex file to add to the tex file preamble ;
+% 
+% output: 
+%   beamer_presentation:
+%     includes:
+%       in_header: mypreamble.tex
+% 
+% In mypreamble.tex, add:
+% 
+% \def\begincols{\begin{columns}}
+% \def\begincol{\begin{column}}
+% \def\endcol{\end{column}}
+% \def\endcols{\end{columns}}
+% 
+% Finally, in the Rmd file, use this kind of syntax:
+% 
+% ## Two Column Layout
+% 
+% \begincols
+%   \begincol{.48\textwidth}
+% 
+% This slide has two columns.
+% 
+%   \endcol
+% \begincol{.48\textwidth}
+% 
+% ```{r pressure}
+% plot(pressure)
+% ```
+% 
+%   \endcol
+% \endcols
+\def\begincols{\begin{columns}}
+\def\begincol{\begin{column}}
+\def\endcol{\end{column}}
+\def\endcols{\end{columns}}

vhk.Rmd

@@ -1,14 +1,15 @@
 ---
 title: "Vorhofkatheter-Statistik"
 author: "Daniel Kraus"
-date: '2018-12-30'
+date: '2018-12-29'
 output:
   ioslides_presentation: default
+  slidy_presentation: default
   beamer_presentation: default
 ---
 
 ```{r setup, include=FALSE}
-knitr::opts_chunk$set(echo = FALSE)
+knitr::opts_chunk$set(echo = FALSE, warning = FALSE)
 library(tidyverse)
 
 raw_data = read_csv('vhk.csv') %>%
@@ -28,7 +29,7 @@ cath_by_year %>%
   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)
+  labs(x = NULL, y = "Anzahl Katheter")
 ```
 
 ## Alter der Patienten
@@ -39,7 +40,7 @@ raw_data %>%
   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)
+  labs(x = NULL, y = "Jahre")
 ```
 
 ## Geschlecht der Patienten
@@ -52,13 +53,53 @@ raw_data %>% group_by(Year) %>% summarise(PercentFemale = sum(Sex == "weiblich")
   labs(x = NULL, y = "Anteil Frauen")
 ```
 
+## Katheterlokalisation
+Ist da ein Trend hin zu immer mehr Kathetern von links?!
+```{r insertion_site}
+raw_data %>% mutate(Side = factor(Side, levels = c("rechts", "links"))) %>%
+  ggplot(aes(x = Year)) +
+  facet_grid(InsertionSite ~ Side) +
+  geom_bar() +
+  labs(x = NULL, y = "Anzahl Katheter")
+```
+
+## Anteil der Arztrollen
+Um 2014 herum haben einige die Facharztprüfung abgelegt, ist das der Grund für die Auffälligkeit 2015/2016?
+```{r percent_residents}
+raw_data %>% group_by(Year) %>% 
+  summarize(Assistenzarzt = sum(SurgeonRole == "Assistenzarzt") / n(),
+            Facharzt = sum(SurgeonRole == "Facharzt") / n(),
+            Oberarzt = sum(SurgeonRole == "Oberarzt") / n()) %>%
+  gather(key = Role, value = Percent, Assistenzarzt, Facharzt, Oberarzt) %>%
+  ggplot(aes(x = Year, y = Percent)) +
+  scale_x_continuous(breaks = seq(from = first_year, to = last_year, by = 1)) +
+  scale_y_continuous(labels = scales::percent_format(accuracy = 1)) +
+  facet_grid(Role ~ .) +
+  geom_col() +
+  labs(x = NULL, y = "Anteil in den gelegten Kathetern")
+```
+
+## Hitparade der Durchleuchtungsdauern
+```{r greatest_fluoroscopy}
+raw_data %>%
+  group_by(Surgeon) %>%
+  summarize(FluoroscopyIndex = median(InsertionFluoroscopyDuration, na.rm = TRUE)) %>%
+  arrange(desc(FluoroscopyIndex)) %>%
+  top_n(-10, FluoroscopyIndex) %>%
+  mutate(Surgeon = factor(Surgeon, levels = Surgeon)) %>%
+  ggplot(aes(x = Surgeon, y = FluoroscopyIndex)) +
+  geom_col() +
+  coord_flip() +
+  labs(x = NULL, y = "Median der Durchleuchtungsdauer [s]")
+```
+
 ## 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)
+  labs(x = NULL, y = "Gesamtzahl Katheter")
 ```
 
 ## Hitparade der Assistenten
@@ -67,6 +108,6 @@ raw_data %>% count(Assistant) %>% arrange(n) %>% top_n(10, n) %>% mutate(Assista
   ggplot(aes(x = Assistant, y = n)) +
   geom_col() +
   coord_flip() +
-  labs(x = NULL, y = NULL)
+  labs(x = NULL, y = "Gesamtzahl Katheter")
 ```