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Visualize data in R

The R ecosystem offers multiple graphing libraries that come packed with many different features. By default, every Apache Spark Pool in Microsoft Fabric contains a set of curated and popular open-source libraries. Add or manage extra libraries or versions by using the Microsoft Fabric library management capabilities.

Prerequisites

  • Open or create a notebook. To learn how, see How to use Microsoft Fabric notebooks.

  • Set the language option to SparkR (R) to change the primary language.

  • Attach your notebook to a lakehouse. On the left side, select Add to add an existing lakehouse or to create a lakehouse.

ggplot2

The ggplot2 library is popular for data visualization and exploratory data analysis.

Screenshot of ggplot2 scatterplot.

%%sparkr
library(ggplot2)
data(mpg, package="ggplot2") 
theme_set(theme_bw()) 

g <- ggplot(mpg, aes(cty, hwy))

# Scatterplot
g + geom_point() + 
  geom_smooth(method="lm", se=F) +
  labs(subtitle="mpg: city vs highway mileage", 
       y="hwy", 
       x="cty", 
       title="Scatterplot with overlapping points", 
       caption="Source: midwest")

rbokeh

rbokeh is a native R plotting library for creating interactive graphics.

Screenshot of rbokeh points.

library(rbokeh)
p <- figure() %>%
  ly_points(Sepal.Length, Sepal.Width, data = iris,
    color = Species, glyph = Species,
    hover = list(Sepal.Length, Sepal.Width))
p

R Plotly

Plotly is an R graphing library that makes interactive, publication-quality graphs.

Screenshot of plot line.

library(plotly) 

fig <- plot_ly() %>% 
  add_lines(x = c("a","b","c"), y = c(1,3,2))%>% 
  layout(title="sample figure", xaxis = list(title = 'x'), yaxis = list(title = 'y'), plot_bgcolor = "#c7daec") 

fig

Highcharter

Highcharter is an R wrapper for Highcharts JavaScript library and its modules.

Screenshot of highchart scatter.

library(magrittr)
library(highcharter)
hchart(mtcars, "scatter", hcaes(wt, mpg, z = drat, color = hp)) %>%
  hc_title(text = "Scatter chart with size and color")