R Notebook

##Tendencies of Suicide Rates Among Different Gender and Age Groups in Population of Diiferent Countries

I will use the Suicide Rates Overview 1985 to 2016 data from Kaggle that compares socio-economic information with suicide rates by year and country to explore tendencies of suicides in different countries, age groups, and gender.

Importing data for analysis:

library (readr)
master<-read_csv("C:/Users/Marcy/Documents/soc 712/master.csv")
head (master)

library(ggplot2)
library(ggthemes)
library(babynames)
library(Zelig)
library(ggrepel)
library(HistData)
library(tidyverse)

ggplot(master, aes(x = suicides_no, y=generation)) + 
  geom_path()

ggplot(master, aes(x = suicides_no, y=sex)) + 
  geom_path()

names (master)

m <- rename(master, rate = "suicides/100k pop")

ggplot(m, aes(x = rate, y=age)) + 
  geom_path()

  

Masrate_plot <- ggplot(data = m, aes(x = rate, y = age)) +
  geom_line(aes(color = rate), size = 12)

Masrate_plot

Masrate <- m %>%
  filter(sex %in% c("35-54 years", "75+years", "25-34 years"))

Masrate_plot <- ggplot(data = m, aes(x = rate, y = sex)) +
  geom_line(aes(color = rate), size = 12)

Masrate_plot


Masrate_plot + theme_tufte()

library(ggthemes)
library(gganimate)
library(tidyverse)
library(dplyr)
library(viridis)

graph_data <- ggplot(master, mapping =aes(x= year, y = suicides_no))

graph1 <- graph_data + geom_smooth() 

graph1 + labs(title = 'Trend of World Suicide Frequency Over the Years') + theme_tufte()

library (dplyr)
library (ggthemes)

gg2<-ggplot(master, aes(y = suicides_no, x = age) ) + geom_point(color='green') + geom_line(color='pink') +theme_calc() +stat_smooth(method = "lm",color="orange")+labs(title = 'Rate of Suicides Per Age Group')
library(plotly)
ggplotly(gg2)

library (ggplot2)
library (gganimate)
library (gifski)
library (devtools)
library (gapminder)
library (png)

master %>%
ggplot(aes(x=factor(year),y=suicides_no, fill = suicides_no)) +
  geom_col(alpha = 0.8) +
  scale_size(range = c(4, 12)) + 
  guides(fill=guide_legend(title="Suicide Rate in Years"))+
  labs(title = 'Suicide Rate in Years',
       subtitle='Date: {frame_time}', 
       x = 'year', 
       y = 'rate')+
  transition_time(year)+
  coord_flip()+
  theme_gray()

master %>%
ggplot(aes(x=factor(sex),y=suicides_no, fill = suicides_no)) +
  geom_col(alpha = 0.8) +
  scale_size(range = c(4, 12)) + 
  guides(fill=guide_legend(title="Suicide Rate in Years"))+
  labs(title = 'Suicide Rate By Gender in Years',
       subtitle='Date: {frame_time}', 
       x = 'gender', 
       y = 'rate of suicides')+
  transition_time(year)+
  coord_flip()+
  theme_gray()

```

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