[MSR] RTVS - Import Data from URL and Draw an interactive 3D plot

/*******************************************************************************************************************
-- Title : [MSR] RTVS - Import Data from URL and Draw an interactive 3D plot
-- Reference : microsoft.com
-- Key word : microsoft r rtvs url ggplot ggplot2 rcurl geturl read.csv revoscaler rximport xdf quakes 
                  geom_point coord_map scale_colour_gradient ggplotgrob grid.draw plot3d with
*******************************************************************************************************************/

-- Chart

-- Microsoft R

# **************************************************
# -- Import Data from URL to Dataframe
# **************************************************
# This script shows how to import data into R that is referenced by a URL.
 
# -- Install the RCurl package if it's not already installed.
if (!require("RCurl", quietly = TRUE)) 
    install.packages("RCurl")
 
# - Load packages.
library("RCurl", quietly = TRUE)
 
# -- A URL contains the raw data.
github <- "https://raw.githubusercontent.com/brohrer-ms/RTVS-docs/master/examples/MRS_and_Machine_Learning/Datasets/"
inputDataURL <- paste0(github, "Flight_Delays_Sample.csv")
 
# -- Download data from the URL.
inputData <- getURL(inputDataURL)
 
# -- Read downloaded data into a data frame.
df <- read.csv(text = inputData, na.strings = "NA", stringsAsFactors = FALSE)
 
# -- Review the first 6 rows of data.
head(df)
 
 
# **************************************************
# -- Import Data from URL to xdf
# **************************************************
 
# -- Note messages, if it's not installed
if (!require("RevoScaleR")) {
    cat("RevoScaleR package does not seem to exist. 
        \nThis means that the functions starting with 'rx' will not run. 
        \nIf you have Microsoft R Server installed, 
        \nplease switch the R engine.
        \nFor example, in R Tools for Visual Studio: 
        \nR Tools -> Options -> R Engine. 
        \nIf Microsoft R Server is not installed, you can download it from: 
        \nhttps://www.microsoft.com/en-us/server-cloud/products/r-server/
        \n")
 
    quit()
}
 
# -- A URL contains the raw data.
github <- "https://raw.githubusercontent.com/brohrer-ms/RTVS-docs/master/examples/MRS_and_Machine_Learning/Datasets/"
inputDataURL <- paste0(github, "Flight_Delays_Sample.csv")
 
# -- Create a temporary directory to store the intermediate .xdf files.
tempdir()                         # "C:\\Users\\Hayden\\AppData\\Local\\Temp\\Rtmpkb2mcH"
td <- tempdir()
 
# -- Read a downloaded .csv file into a RxXdfData object.
outFile <- paste0(td, "/data.xdf")
df_xdf <- rxImport(inData = inputDataURL, outFile = outFile,
                   missingValueString = "M", stringsAsFactors = FALSE)
 
# Review the first 6 rows of data.
head(df_xdf)
 
 
# **************************************************
# -- Draw it using ggplot2
# **************************************************
 
# -- Read the help page for more information
? quakes
 
# -- Inspect the structure of the data (a data frame with 5 columns)
str(quakes)
head(quakes)
 
# -- install and load the packages
suppressWarnings(if (!require("ggplot2")) install.packages("ggplot2"))
library("ggplot2")
 
suppressWarnings(if (!require("rgl")) install.packages("rgl"))
library("rgl")
 
suppressWarnings(if (!require("mapproj")) install.packages("mapproj"))
library("mapproj")
 
# The package "gtable" allows you to work with objects called grob tables.
# A grob table captures all the information needed to layout grobs in a table
# structure. It supports row and column spanning, offers some tools to
# automatically figure out the correct dimensions, and makes it easy to align
# and combine multiple tables. 
suppressWarnings(if (!require("gtable")) install.packages("gtable"))
library(gtable)
 
# Plot longitude and latitude of quakes.
# To create a plot, you have to specify the data, then map aesthetics to 
# columns in your data. In this example, you map the column long to the x-axis
# and lat to the y-axis.
# Then you add a layer with points (geom_point) and a layer to plot maps.
p0 <- ggplot(quakes, aes(x = long, y = lat)) +
    geom_point() +
    coord_map()
p0
 
# You can use a number of different aesthetics, for example colour or size
# of the points.
 
# Map the depth column to the colour aesthetic.
p1 <- ggplot(quakes, aes(x = long, y = lat)) +
    geom_point(aes(colour = depth)) +
    coord_map()
p1
 
# Add size for magnitude. The bigger the magnitude, the larger the point.
p2 <- ggplot(quakes, aes(x = long, y = lat)) +
    geom_point(aes(colour = depth, size = mag)) +
    coord_map()
p2
 
# You can control the transparancy of a plot object with the alpha aesthetic.
# High values of alpha (close to 1) are opaque, while low values (close to 0)
# are translucent.
# Add alpha level to hide overplotting, thus revealing detail.
p3 <- ggplot(quakes, aes(x = long, y = lat)) +
    geom_point(aes(colour = depth, size = mag), alpha = 0.25) +
    coord_map()
p3
 
# Change colour gradient by adding a gradient scale.
p4 <- ggplot(quakes, aes(x = long, y = lat)) +
    geom_point(aes(colour = depth, size = mag), alpha = 0.25) +
    coord_map() +
    scale_colour_gradient(low = "blue", high = "red")
p4
 
# Add a plot title
p5 <- ggplot(quakes, aes(x = long, y = lat)) +
    geom_point(aes(colour = depth, size = mag), alpha = 0.25) +
    scale_colour_gradient(low = "blue", high = "red") +
    ggtitle("Distribution of earthquakes near Fiji") +
    coord_map()
p5
 
# Now plot multiple plots on the same graphic
# The package "grid" is built into R and allows you to take control of the 
# plotting area. A grob is the abbreviation for "graphical object", and the 
# function ggplotGrob() in ggplot2 converts a ggplot2 object into a grob.
# You can then use the grid functions to combine your ggplot objects.
theme_set(theme_grey(12) + theme(legend.key.size = unit(0.5, "lines")))
 
library(grid)
plot.new()
grid.draw(cbind(
    ggplotGrob(p1),
    ggplotGrob(p2),
    ggplotGrob(p3),
    size = "last"
    ))
    
plonglat <- ggplot(quakes, aes(x = long, y = lat, size = mag, col = depth)) +
    geom_point(alpha = 0.5) +
    ggtitle("Top view")
 
plongdep <- ggplot(quakes, aes(x = long, y = -depth, size = mag, col = depth)) +
    geom_point(alpha = 0.5) +
    ggtitle("Side view")
 
platdep <- ggplot(quakes, aes(x = depth, y = lat, size = mag, col = depth)) +
    geom_point(alpha = 0.5) +
    ggtitle("Side view")
 
# Next, define a gtable and add grobs to the table.
gt <- gtable(widths = unit(rep(1, 2), "null"),
             heights = unit(rep(1, 2), "null"))
gt <- gtable_add_grob(gt,
                      grobs = list(
                        ggplotGrob(plonglat),
                        ggplotGrob(platdep),
                        ggplotGrob(plongdep)
                      ),
                      l = c(1, 2, 1), # left extent of the grobs
                      t = c(1, 1, 2) # top extent of the grobs
)
plot.new()
grid.draw(gt)
 
# Finally, you can plot the data in an interactive 3D plot, using package rgl.
# Note this will open a seperate window with your plot.
# This window is interactive - you can click and drag in the window,
# thus changing the orientation of the data in 3 dimensions.
with(quakes, plot3d(lat, long, - depth, col = mag))