Related Setup: https://gist.github.com/hofmannsven/6814278
Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/
state,area_nr,area_name,total_n,germans_n,foreigner_n,pop_move_n,pop_migr_background_n,income,unemp_n,votes_total,afd_votes,afd_prop,east,state_id,total_n_z,germans_n_z,foreigner_n_z,pop_move_n_z,pop_migr_background_n_z,income_z,unemp_n_z,votes_total_z,afd_votes_z,afd_prop_z | |
Schleswig-Holstein,1,Flensburg – Schleswig,282800,266700,16100,3478440,28280,20265,20361,170396,11647000,0.06835254348693631,0,15,0.2103609895241015,0.7384953705950867,-0.6866607746103975,-0.23405819513595597,-0.8241784980071718,-0.331229037339419,0.5294325736242255,0.7420571802149715,-0.9559380206641114,-1.0844472782356187 | |
Schleswig-Holstein,2,Nordfriesland – Dithmarschen Nord,232300,219700,12600,3066360,18584,22159,16725,138075,9023000,0.06534854245880861,0,15,-1.12317180392684,-0.9301927624096695,-0.8739260711324136,-0.5246213450924033,-1.1451159729868976,0.4782205523605706,-0.0022599637360526327,-0.8725210301240619,-1.2691398862049443,-1.1394454488402648 | |
Schleswig-Holstein,3,Steinburg – Dithmarschen Süd,220800,209800,11000,2627520,203 |
afd_votes | votes_total | foreigner_n | |
---|---|---|---|
11647 | 170396 | 16100 | |
9023 | 138075 | 12600 | |
11176 | 130875 | 11000 | |
11578 | 156268 | 9299 | |
10390 | 150173 | 25099 | |
11161 | 130514 | 13000 | |
15977 | 186372 | 26000 | |
17166 | 191937 | 18300 | |
11780 | 137273 | 9400 |
Related Setup: https://gist.github.com/hofmannsven/6814278
Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/
# Plot path diagram with {DiagrammeR} | |
data(Wage, package = "ISLR") #load data | |
lm_wage <- lm(wage ~ health + age + health:age, data = Wage) # run linear model | |
summary(lm_wage) | |
library(semPlot) # plot path diagram with {semPlot} | |
semPaths(lm_wage, whatLabel = "est", vsize.man = 16, edge.label.cex=0.6) |
############################################################################### | |
### Beispiel-Analyse des Datensatzes "tips" | |
### von Sebastian Sauer, letztes Update: 2016-01-18 | |
### Zugang zu den Daten: Der Datensatz findet sich im Paket "reshape2" | |
############################################################################### | |
# Hinweis: Es ist ganz normal, Syntax/Befehle nachzuschlagen :) | |
# Eine Möglichkeit dazu ist mit help(Befehl), z.B. | |
help(library) # oder mit google :) |
library(dplyr) | |
data(Wage, package = "ISLR") | |
Wage %>% | |
mutate(wage_f = ntile(wage, 2)) %>% # bin it | |
group_by(wage_f, health, race) %>% | |
summarise(count = n()) %>% | |
ggplot(aes(x = factor(wage_f), y = count, fill = race)) + | |
geom_bar(stat = "identity") + |
#Barplots with exact numbers | |
data(tips, package = "reshape2") # load some data | |
library(dplyr) | |
library(tidyr) | |
library(ggplot2) | |
tips %>% |
SLIDES := $(patsubst %.md,%.md.slides.pdf,$(wildcard *.md)) | |
HANDOUTS := $(patsubst %.md,%.md.handout.pdf,$(wildcard *.md)) | |
all : $(SLIDES) $(HANDOUTS) | |
%.md.slides.pdf : %.md | |
pandoc $^ -t beamer --slide-level 2 -o $@ | |
%.md.handout.pdf : %.md | |
pandoc $^ -t beamer --slide-level 2 -V handout -o $@ |
# plot normal distribution with ggplot2, simply | |
library(cowplot) | |
p1 <- ggplot(data = data.frame(x = c(-3, 3)), aes(x)) + | |
stat_function(fun = dnorm, n = 101, args = list(mean = 0, sd = 1)) + ylab("") + | |
scale_y_continuous(breaks = NULL) | |
p1 |
# Exam grading, as a convenience function for teachers | |
# Sebastian Sauer | |
# Stand: 2016-05-20 | |
# need to be installed upfront with "install.packages()" | |
library(ggplot2) | |
library(car) | |
library(tidyr) |