library(tidyverse)
library(plotly)

load("~/Documents/cses_imd")

cses_cz13 <- cses_imd %>%
  filter(IMD1004 == "CZE_2013") %>%
  filter(IMD2001_1 < 150) %>%
  filter(edu < 6) %>%
  filter(dem <= 6)

#histogram
cses_cz13 %>%
  ggplot(aes(x=IMD2001_1)) +
  geom_histogram(bins=10)

#density
cses_cz13 %>%
  ggplot(aes(x=IMD2001_1)) +
  geom_density()


#boxplot

cses_cz13 %>%
  ggplot(aes(y=IMD2001_1)) +
  geom_boxplot()

cses_cz13 %>%
  ggplot(aes(y=IMD2001_1, x= factor(edu))) +
  geom_boxplot()

cses_cz13 %>%
  ggplot(aes(y=IMD2001_1, x= factor(edu))) +
  geom_boxplot() +
  geom_point()

#jitter
cses_cz13 %>%
  ggplot(aes(y=IMD2001_1, x= factor(edu))) +
  geom_jitter()+
  geom_boxplot()
  

cses_cz13 %>%
  ggplot(aes(y=IMD2001_1, x= factor(edu))) +
  geom_boxplot() +
  geom_jitter(aes(alpha=0.5, color="red"))

cses_cz13 %>%
  ggplot(aes(y=IMD2001_1, x= factor(edu))) +
  geom_jitter(aes(alpha=0.5, col="red")) +
  geom_boxplot()

#bar plot
cses_cz13 %>%
  ggplot(aes(fill=factor(IMD2002), x= factor(edu))) +
  geom_bar()

cses_cz13 %>%
  ggplot(aes(fill=factor(IMD2002), x= factor(edu))) +
  geom_bar()+
  scale_fill_manual(values=c("#999999", "#E69F00", "#56B4E9"))

cses_cz13 %>%
  ggplot(aes(fill=factor(IMD2002), x= factor(edu))) +
  geom_bar(position = "fill")+
  scale_fill_manual(values=c("#999999", "#E69F00", "#56B4E9"))

cses_cz13 %>%
  filter(IMD2002< 3) %>%
  ggplot(aes(fill=factor(IMD2002), x= factor(edu))) +
  geom_bar(position = "fill")+
  scale_fill_manual(values=c("#999999", "#E69F00"))

cses_cz13 %>%
  filter(IMD2002< 3) %>%
  ggplot(aes(fill=factor(IMD2002), x= factor(edu))) +
  geom_bar(position = "fill")+
  scale_fill_brewer(palette = "Set1")

#Diverging
#BrBG, PiYG, PRGn, PuOr, RdBu, RdGy, RdYlBu, RdYlGn, Spectral
#
#Qualitative
#Accent, Dark2, Paired, Pastel1, Pastel2, Set1, Set2, Set3
#
#Sequential
#Blues, BuGn, BuPu, GnBu, Greens, Greys, Oranges, OrRd, PuBu, PuBuGn, PuRd, Purples, RdPu, Reds, YlGn, YlGnBu, YlOrBr, YlOrRd

#scatter plot
cses_cz13 <- cses_cz13 %>%
  mutate(new = IMD2001_1 + rnorm(1521, sd=3))

cses_cz13 %>%
  ggplot(aes(y=IMD2001_1, x= new)) +
  geom_point()

cses_cz13 %>%
  ggplot(aes(y=IMD2001_1, x= new)) +
  geom_point() +
  geom_smooth(method="lm")

cses_cz13 %>%
  ggplot(aes(y=IMD2001_1, x= new, shape = factor(IMD2002))) +
  geom_point()

cses_cz13 %>%
  #filter(IMD2002< 3) %>%
  ggplot(aes(y=IMD2001_1, x= new)) +
  geom_point() +
  geom_smooth(method="lm") + 
  facet_grid(cols = vars(factor(IMD2002)))

#save to object
plot1 <- cses_cz13 %>%
  filter(IMD2002< 3) %>%
  sample_n(200) %>%
  ggplot(aes(y=IMD2001_1, x= new, shape = factor(IMD2002), color=factor(IMD2002))) +
  geom_point(alpha=.9, size=5, color="black") +
  geom_point(alpha=.6, size=4) +
  geom_smooth(method="lm", color = "green", size=1)

plot1

#labs
plot1 +
  labs(x="My new variable", title = "My Plot", shape = "legend name")

plot1 +
  labs(x="New Name", title = "My Plot", shape = "legend name", color = "legend 2")+
  scale_shape_manual(values=c(15,19), labels=c("Male","Female"))

plot1 +
  theme_bw() +
  theme(legend.position="bottom") +
  labs(x="New Name", title = "My Plot", shape = "legend name", color = "legend 2")+
  scale_shape_manual(values=c(15,19), labels=c("Male","Female")) +
  guides(color = "none")

final_plot <- plot1 +
  theme_bw() +
  theme(legend.position="bottom") +
  labs(x="New Name", title = "My Plot", shape = "legend name", color = "legend 2")+
  scale_shape_manual(values=c(15,19), labels=c("Male","Female")) +
  guides(color = "none")

#export
ggsave("final_plot.png")
ggsave("final_plot.png", width = 4, height = 4, dpi = 800)

#interactive plots
plot2 <- cses_cz13 %>%
  filter(IMD2002< 3) %>%
  sample_n(200) %>%
  ggplot(aes(y=IMD2001_1, x= new, shape = factor(IMD2002), color=factor(IMD2002))) +
  geom_point(alpha=.9, size=3)

ggplotly(plot2)

#dplyr + ggplot2

cses_imd_filter %>%
  group_by(IMD1004) %>%
  select(edu, dem) %>%
  summarise_all(mean) %>%
  ggplot(aes(x=edu, y=dem, label=IMD1004))+
  geom_point()+
  geom_text()

library(ggrepel)

cses_imd_filter %>%
  group_by(IMD1004) %>%
  select(edu, dem) %>%
  summarise_all(mean) %>%
  ggplot(aes(x=edu, y=dem, label=IMD1004))+
  geom_point()+
  geom_smooth(method="lm", se=F)+
  geom_text_repel()