df_취업률_500 <- readRDS("df_취업률_500.rds")
df_취업률 <- readRDS( "df_취업률.rds")
df_covid19 <- readRDS("df_covid19.rds")
df_covid19_100 <- readRDS("df_covid19_100.rds")
df_covid19_100_wide <- readRDS("df_covid19_100_wide.rds")
df_covid19_stat <- readRDS("df_covid19_stat.rds")pl_part2_ch3
ch3. Trace
데이터 불러오기
library(plotly) Loading required package: ggplot2
Attaching package: 'plotly'
The following object is masked from 'package:ggplot2':
last_plot
The following object is masked from 'package:stats':
filter
The following object is masked from 'package:graphics':
layout
df_취업률_500 |>
filter(졸업자수 < 500) |>
plot_ly() |> ## Plotly 초기화
## scatter 트레이스에 makers 모드 설정
add_trace(type = 'scatter', mode = 'markers',
x = ~졸업자수, y = ~취업자수, name = ~대계열, ## name 속성 설정
## marker 사이즈와 색상 설정
marker = list(size = 3, color = 'darkblue')) ##add_trace에는 반드시 type 지정Opacity, alpha
df_취업률_500 |> plot_ly() |>
add_trace(type = 'scatter', mode = 'markers',
x = ~졸업자수, y = ~취업자수,
## marker 내부에서 opacity 설정
marker = list(opacity = 0.3, color = 'darkblue'))df_취업률_500 |> plot_ly() |>
add_trace(type = 'scatter', mode = 'markers',
x = ~졸업자수, y = ~취업자수,
marker = list(color = 'darkblue'),
## marker 외부에서 opacity 설정
opacity = 0.3)Showlegend
df_취업률_500 |>
plot_ly() |>
add_trace(type = 'scatter', mode = 'markers',
x = ~졸업자수, y = ~취업자수, name = ~대계열, ##name을 컬러 구분으로 인식
showlegend = FALSE) ## showlegend를 FALSE로 설정df_취업률_500 |>
plot_ly() |>
add_trace(type = 'scatter', mode = 'markers',
x = ~졸업자수, y = ~취업자수, name = ~대계열,
showlegend = T) ## showlegend를 TRUE로 설정text, textposition, texttemplate
## 긴 형태의 100일간 코로나19 데이터 중에
df_covid19_100 |>
## 국가명으로 그룹화
group_by(location) |>
## 확진자수의 합계를 new_cases로 산출
summarise(new_cases = sum(new_cases)) |>
## X축을 location, Y축과 text를 new_case로 매핑
plot_ly() |>
add_trace(type = 'bar', ## bar 트레이스 설정
x = ~location, y = ~new_cases,
text = ~new_cases) ## 텍스트 설정df_covid19_100 |>
group_by(location) |>
summarise(new_cases = sum(new_cases)) |>
plot_ly() |>
add_trace(type = 'bar', x = ~location, y = ~new_cases, text = ~new_cases,
## textposition을 'inside'로 설정
textposition = 'inside')#######################################
df_covid19_100 |>
group_by(location) |>
summarise(new_cases = sum(new_cases)) |>
plot_ly() |>
add_trace(type = 'bar', x = ~location, y = ~new_cases, text = ~new_cases,
## textposition을 'outside'로 설정
textposition = 'outside')#######################################
df_covid19_100 |>
group_by(location) |>
summarise(new_cases = sum(new_cases)) |>
plot_ly() |>
add_trace(type = 'bar', x = ~location, y = ~new_cases, text = ~new_cases,
## textposition을 'auto'로 설정
textposition = 'auto')#######################################
df_covid19_100 |>
group_by(location) |>
summarise(new_cases = sum(new_cases)) |>
plot_ly() |>
add_trace(type = 'bar', x = ~location, y = ~new_cases, text = ~new_cases,
## textposition을 'none'으로 설정
textposition = 'none')texttemplete
df_covid19_100 |>
group_by(location) |>
summarise(new_cases = sum(new_cases)) |>
plot_ly() |>
add_trace(type = 'bar', x = ~location, y = ~new_cases, text = ~new_cases,
textposition = 'inside',
texttemplate = '확진자수:%{text:,}') ## texttemplate를 설정hoverinfo, hovertext, hovertemplate
df_취업률_500 |>
plot_ly() |>
add_trace(type = 'scatter', mode = 'markers',
x = ~졸업자수, y = ~취업자수,
hoverinfo = 'y') ## hoverinfo 설정hovertext
df_취업률_500 |>
plot_ly() |>
add_trace(type = 'scatter', mode = 'markers',
x = ~졸업자수, y = ~취업자수,
## hovertext의 설정
hovertext = ~paste0('중계열:', 중계열, '\n', '소계열:', 소계열))hovertemplete
df_취업률_500 |>
plot_ly() |>
add_trace(type = 'scatter', mode = 'markers',
x = ~졸업자수, y = ~취업자수, hovertext = ~대계열,
## hovertemplate의 설정
hovertemplate = ' 졸업자:%{x}, 취업자:%{y}, 대계열:%{hovertext}')