Quarto Basics

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DK

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Quarto

Quarto enables you to weave together content and executable code into a finished document. To learn more about Quarto see https://quarto.org.

Running Code

When you click the Render button a document will be generated that includes both content and the output of embedded code. You can embed code like this:

[1] 2

You can add options to executable code like this

[1] 4

The echo: false option disables the printing of code (only output is displayed).

library(tidyverse)
smaller <- diamonds %>%
  filter(carat <= 2.5)
smaller
# A tibble: 53,814 × 10
   carat cut       color clarity depth table price     x     y     z
   <dbl> <ord>     <ord> <ord>   <dbl> <dbl> <int> <dbl> <dbl> <dbl>
 1  0.23 Ideal     E     SI2      61.5    55   326  3.95  3.98  2.43
 2  0.21 Premium   E     SI1      59.8    61   326  3.89  3.84  2.31
 3  0.23 Good      E     VS1      56.9    65   327  4.05  4.07  2.31
 4  0.29 Premium   I     VS2      62.4    58   334  4.2   4.23  2.63
 5  0.31 Good      J     SI2      63.3    58   335  4.34  4.35  2.75
 6  0.24 Very Good J     VVS2     62.8    57   336  3.94  3.96  2.48
 7  0.24 Very Good I     VVS1     62.3    57   336  3.95  3.98  2.47
 8  0.26 Very Good H     SI1      61.9    55   337  4.07  4.11  2.53
 9  0.22 Fair      E     VS2      65.1    61   337  3.87  3.78  2.49
10  0.23 Very Good H     VS1      59.4    61   338  4     4.05  2.39
# ℹ 53,804 more rows
smaller %>%
  ggplot(aes(x=carat))+
  geom_bar(binwidth=0.01)

Interactive Plots

library(plotly)
Warning: package 'plotly' was built under R version 4.5.2

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
library(ggplot2)

data (economics)
plot_ly(
  data = economics,
  x = ~date,
  y = ~unemploy,
  type="scatter",
  mode = "lines"
) %>%
  layout(
    xaxis = list(title = "Date"),
    yaxis = list(title = "Number of Unemployed")
  )
plot_ly(
  data = economics,
  x= ~date,
  y= ~unemploy,
  type = "scatter",
  mode = "makers"
)
plot_ly(
  data = economics, 
  x = ~unemploy,
  type = "histogram"
)
library(leaflet)

leaflet() %>%
  addTiles () %>%
  addMarkers(
    lng = -84.39,
    lat = 33.75,
    popup = "Atlanta"
  )
leaflet() %>%
  addTiles() %>%
  addMarkers(
    lng = -84.5184,
    lat = 33.9384,
    popup= "KSU Marietta"
  )

Interactive Tables

subcars <- mtcars[1:5,1:4]

knitr::kable(subcars,
             col.names = c("Mile/Gallon","#Cylinders", 
                           "Eng Displacement","Horsepower"),
             row.names = F,
             caption = "Car Data")
Car Data
Mile/Gallon #Cylinders Eng Displacement Horsepower
21.0 6 160 110
21.0 6 160 110
22.8 4 108 93
21.4 6 258 110
18.7 8 360 175

Interactive Tables

library(DT)
datatable(mpg)