radiant.data (version 0.8.0)

visualize: Visualize data using ggplot2

Description

Visualize data using ggplot2 http://docs.ggplot2.org/current/

Usage

visualize(dataset, xvar, yvar = "", comby = FALSE, combx = FALSE,
  type = "dist", facet_row = ".", facet_col = ".", color = "none",
  fill = "none", size = "none", bins = 10, smooth = 1, fun = "mean",
  check = "", axes = "", alpha = 0.5, ylim = "none", data_filter = "",
  shiny = FALSE, custom = FALSE)

Arguments

dataset

Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant

xvar

One or more variables to display along the X-axis of the plot

yvar

Variable to display along the Y-axis of the plot (default = "none")

comby

Combine yvars in plot (TRUE or FALSE, FALSE is the default)

combx

Combine xvars in plot (TRUE or FALSE, FALSE is the default)

type

Type of plot to create. One of Distribution ('dist'), Density ('density'), Scatter ('scatter'), Surface ('surface'), Line ('line'), Bar ('bar'), or Box-plot ('box')

facet_row

Create vertically arranged subplots for each level of the selected factor variable

facet_col

Create horizontally arranged subplots for each level of the selected factor variable

color

Adds color to a scatter plot to generate a 'heat map'. For a line plot one line is created for each group and each is assigned a different color

fill

Display bar, distribution, and density plots by group, each with a different color. Also applied to surface plots to generate a 'heat map'

size

Numeric variable used to scale the size of scatter-plot points

bins

Number of bins used for a histogram (1 - 50)

smooth

Adjust the flexibility of the loess line for scatter plots

fun

Set the summary measure for line and bar plots when the X-variable is a factor (default is "mean"). Also used to plot an error bar in a scatter plot when the X-variable is a factor. Options are "mean" and/or "median"

check

Add a regression line ("line"), a loess line ("loess"), or jitter ("jitter") to a scatter plot

axes

Flip the axes in a plot ("flip") or apply a log transformation (base e) to the y-axis ("log_y") or the x-axis ("log_x")

alpha

Opacity for plot elements (0 to 1)

ylim

Set limit for y-axis

data_filter

Expression used to filter the dataset. This should be a string (e.g., "price > 10000")

shiny

Logical (TRUE, FALSE) to indicate if the function call originate inside a shiny app

custom

Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This opion can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and http://docs.ggplot2.org/ for options.

Value

Generated plots

Details

See http://radiant-rstats.github.io/docs/data/visualize.html for an example in Radiant

Examples

visualize("diamonds", "price:x", type = "dist")
visualize("diamonds", "carat:x", yvar = "price", type = "scatter")
## Not run: ------------------------------------
# visualize(dataset = "diamonds", yvar = "price", xvar = c("cut","clarity"),
#   type = "bar", fun = "median")
# visualize(dataset = "diamonds", yvar = "price", xvar = c("cut","clarity"),
#   type = "line", fun = "max")
# visualize(dataset = "diamonds", yvar = "price", xvar = "carat", type = "scatter",
#           size = "table", custom = TRUE) + scale_size(range=c(1,10), guide = "none")
# visualize(dataset = "diamonds", yvar = "price", xvar = "carat", type = "scatter", custom = TRUE) +
#   labs(title = "A scatterplot", x = "price in $")
# visualize(dataset = "diamonds", xvar = "price:carat", custom = TRUE) %>%
#   gridExtra::grid.arrange(grobs = ., top = "Histograms", ncol = 2)
# visualize(dataset = "diamonds", xvar = "cut", yvar = "price", type = "bar",
#   facet_row = "cut", fill = "cut")
## ---------------------------------------------