Flows and Circles

######A1Tuvial Diagrams #Adapted from: https://github.com/corybrunson /ggalluvial #install.packages (“ggalluvial”) library(“ggalluvial”) library(“tidyverse”) library(“packcircles”) library(“dplyr”) library(“ggplot2”) ####21 students are divided in 3 groups, they are men and women, and they get High pass,

#### create some fake data about student performance in classes
#### 21 students are divided in 3 groups, they are men and women, and they get high pass, pass or fail
library("ggalluvial")

## 载入需要的程辑包：ggplot2

library("dplyr")

## 
## 载入程辑包：'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

group1<- tibble::tibble(groupid=groupid<-rep("group1",7),
                studentid=sample(seq(from=1,to=20),7),
                gender=sample(c("M","F"),7,replace=TRUE),
                grades=sample(c("High Pass","Pass","Fail"),7,replace =TRUE))
                
group2<- tibble::tibble(groupid=groupid<-rep("group2",7),
                studentid=sample(seq(from=21,to=30),7),
                gender=sample(c("M","F"),7,replace=TRUE),
                grades=sample(c("High Pass","Pass","Fail"),7,replace =TRUE))
                
group3<- tibble::tibble(groupid=groupid<-rep("group3",7),
                studentid=sample(seq(from=31,to=40),7),
                gender=sample(c("M","F"),7,replace=TRUE),
                grades=sample(c("High Pass","Pass","Fail"),7,replace =TRUE))
                

students<- bind_rows(group1,group2,group3)
students_table<-students%>%
  group_by(groupid,gender,grades) %>%
  count()
  ggplot(students_table, aes(axis1=groupid,axis2=grades,y=n))+
   geom_alluvium(aes(fill=gender))+
   geom_stratum()+
   geom_text(stat="stratum", 
             aes(label=after_stat(stratum)))+
    scale_fill_manual(values=c("purple","green"))

#packed circle figure
#install.packages("packcircles")
####use congress data as an example
#### sample a number of members from the 114th congress
library("tidyverse")

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

## ✓ tibble  3.1.6     ✓ purrr   0.3.4
## ✓ tidyr   1.1.4     ✓ stringr 1.4.0
## ✓ readr   2.1.1     ✓ forcats 0.5.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library("packcircles")
cel <- read_csv(url("https://www.dropbox.com/s/4ebgnkdhhxo5rac/cel_volden_wiseman%20_coursera.csv?raw=1"))

## Rows: 10262 Columns: 38

## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (2): thomas_name, st_name
## dbl (36): thomas_num, icpsr, congress, year, cd, dem, elected, female, votep...

## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

cel_114<- cel %>% dplyr::filter(congress==114)
members<- sample_n(cel_114,25)
packing<- circleProgressiveLayout(members$all_pass,sizetype = 'area')

## Warning in circleProgressiveLayout(members$all_pass, sizetype = "area"): missing
## and/or non-positive sizes will be ignored

members<-add_column(members,packing)
dat.gg<-circleLayoutVertices(packing,npoints = 50)
ggplot()+
  geom_polygon(data=dat.gg,
               aes(x=x,
                   y=y,
                   group=id,
                   fill=as.factor(id),
                   alpha=0.6))+
  geom_text(data=members,
            aes(x=x,
                y=y,
                size=all_pass,
                label=thomas_name))+
  theme(legend.position = "none")+
  coord_equal()

## Warning: Removed 9 rows containing missing values (geom_text).

#### pie charts
Prop<-c(3,7,9,1,2)
pie(Prop)