Plotting in R

Nextjournal’s default R environment comes with the ggplot2 and plotly packages pre-installed. It also includes tidyverse and more to ease working with numerical data. Simply make them available via library(<package name>).

The following examples show how to plot temperature predication data in various scenarios for the Chicago area based on a subset of the OpenNEX DCP30 dataset.

OpenNEX-chicago-climate.csv

Inspecting Data Frames

Inspecting their contents often comes handy when working with data frames. Simply returning a data frame will produce a table viewer that makes it easy to browse the data frame’s contents:

library(tidyverse)
data <- read_csv(OpenNEX-chicago-climate.csv
)
head(data, n=30)

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ggplot2

Check out ggplot2’s documentation for more examples.

library(tidyverse)

# Read in CSV
data <- read_csv(OpenNEX-chicago-climate.csv
)

group <- data %>%
	mutate(
    year = update(Date, day=1, month=1), # Reset dates to beginning of year
    temp = Value - 273.15 # Convert Kelvin to Celsius
  ) %>%
	group_by(year, Scenario) %>% # Group by year and scenario
	summarise(max_temp=max(temp)) # Pick the max temp for each group

model <- first(data["Model"])
title <- paste("Maximum mean temperature for warmest month using model", model)

# Returning the plot tells Nextjournal to display it
ggplot(group, aes(x = year, y = max_temp)) + 
  geom_line(aes(color = Scenario)) +
	labs(
    title = title,
    x = "Years",
    y = "Temperature [Celsius]"
  )

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Plotly

Check out plotly’s documentation for more examples.

library(plotly)

# Read in CSV
data <- read_csv(OpenNEX-chicago-climate.csv
)

group <- data %>%
	mutate(
    year = update(Date, day=1, month=1), # Reset dates to beginning of year
    temp = Value - 273.15 # Convert Kelvin to Celsius
  ) %>%
	group_by(year, Scenario) %>% # Group by year and scenario
	summarise(max_temp=max(temp)) # Pick the max temp for each group

model <- first(data["Model"])
title <- paste("Maximum mean temperature for warmest month using model", model)

# Returning the plot tells Nextjournal to display it
plot_ly(
  group,
  x = ~year,
  y = ~max_temp,
  color = ~Scenario,
  type = "scatter",
  mode = "line"
) %>%
layout(
	title = title,
  xaxis = list(title = "Years"),
  yaxis = list (title = "Temperature [Celsius]")
)

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