InteractiveFlexdashboard

Page 1

Chart A

dat %>% 
  drop_na() %>% 
  filter(year>1979) %>% 
  group_by(year,Party) %>% 
  summarise(passed=sum(all_pass)) %>%
  ggplot(
    aes(x=year,y=passed,fill=Party)) +
    geom_area() +
    labs(title="Number of Bills Passed Since 1980",x="Year",y="All Bills Passed") +
    scale_fill_manual(values=c("blue","red"))

## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.

Page 2

Column

Chart B

(dat%>%
  drop_na()%>%
  filter(congress==110) %>%
    ggplot(
      aes(x=votepct,y=all_pass,color=Party)) +
      geom_point() +
      labs(title="Passage and Vote Pct., 110th Congress",x="Vote Pct.",y="All Pass") +
      scale_color_manual(values=c("blue","red")) +
      geom_smooth()) %>%
  ggplotly()

## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Column

Chart C

(dat%>%
  drop_na()%>%
  filter(congress==110) %>%
    ggplot(
      aes(x=dwnom1,y=all_pass,color=Party)) +
      geom_point() +
      labs(title="Passage and Ideology, 110th Congress",x="DW Nominate.",y="All Pass") +
      scale_color_manual(values=c("blue","red")) +
      geom_smooth(method=lm)) %>%
  ggplotly()

## `geom_smooth()` using formula = 'y ~ x'

Page 3

Input

Chart D

selectInput(inputId="my_state",label="state",choices=sort(unique(dat$st_name)),multiple=TRUE,selected=unique(dat$st_name))

state

AK AL AR AS AZ CA CO CT DC DE FL GA GU HI IA ID IL IN KS KY LA MA MD ME MI MN MO MP MS MT NC ND NE NH NJ NM NV NY OH OK OR PA PR RI SC SD TN TX UT VA VI VT WA WI WV WY

Column

####hint: this figure uses selectInput with the multiple option set to true and with the options set up so that all states are initially selected.

renderPlot(
  dat %>% 
    group_by(st_name) %>% 
    filter(congress==110) %>%
    summarise(passed=sum(all_pass))%>%
    ggplot(
      aes(x=passed,y=st_name)) +
      geom_bar(stat="identity") +
      labs(title="Total Bills Passed by State Delegations, 110th Congress",x="Total Bills Passed Per State",y="State Name")
  
)