Parse an rd file in to staticdocs format.

Usage

parse_rd(topic, package)

Arguments

topic

topic name, as character vector

package

package name, as character vector

Examples

parse_rd("geom_point", "ggplot2")
\-  (10)
  \- title (1)
    " Points, as for a scatterplot
  \- name (1)
    ' geom_point
  \- alias (1)
    ' geom_point
  \- description (2)
    " 
    " The point geom is used to create scatterplots.
  \- usage (4)
    > 
    > geom_point(mapping = NULL, data = NULL,
    > stat = "identity", position = "identity",
    > na.rm = FALSE, ...)
  \- arguments (24)
    " 
    " 
    \- item (2)
      \-  (1)
        " mapping
      \-  (8)
        " The aesthetic mapping, usually constructed
        " with
        \- code (1)
          \- link (1)
            " aes
        " or
        \- code (1)
          \- link (1)
            " aes_string
        " . Only
        " needs to be set at the layer level if you are overriding
        " the plot defaults.
    " 
    " 
    " 
    \- item (2)
      \-  (1)
        " data
      \-  (2)
        " A layer specific dataset - only needed if you
        " want to override the plot defaults.
    " 
    " 
    " 
    \- item (2)
      \-  (1)
        " stat
      \-  (2)
        " The statistical transformation to use on the
        " data for this layer.
    " 
    " 
    " 
    \- item (2)
      \-  (1)
        " position
      \-  (2)
        " The position adjustment to use for
        " overlappling points on this layer
    " 
    " 
    " 
    \- item (2)
      \-  (1)
        " na.rm
      \-  (7)
        " If
        \- code (1)
          > FALSE
        " (the default), removes
        " missing values with a warning.  If
        \- code (1)
          > TRUE
        " silently
        " removes missing values.
    " 
    " 
    " 
    \- item (2)
      \-  (1)
        " ...
      \-  (8)
        " other arguments passed on to
        " 
        \- code (1)
          \- link (1)
            " layer
        " . This can include aesthetics whose
        " values you want to set, not map. See
        \- code (1)
          \- link (1)
            " layer
        " 
        " for more details.
    " 
  \- details (42)
    " 
    " The scatterplot is useful for displaying the relationship
    " between two continuous variables, although it can also be
    " used with one continuous and one categorical variable, or
    " two categorical variables.  See
    \- code (1)
      \- link (1)
        " geom_jitter
    " 
    " for possibilities.
    " 
    " The
    \- emph (1)
      " bubblechart
    " is a scatterplot with a third
    " variable mapped to the size of points.  There are no
    " special names for scatterplots where another variable is
    " mapped to point shape or colour, however.
    " 
    " The biggest potential problem with a scatterplot is
    " overplotting: whenever you have more than a few points,
    " points may be plotted on top of one another. This can
    " severely distort the visual appearance of the plot. There
    " is no one solution to this problem, but there are some
    " techniques that can help.  You can add additional
    " information with
    \- code (1)
      \- link (1)
        " stat_smooth
    " ,
    " 
    \- code (1)
      \- link (1)
        " stat_quantile
    " or
    " 
    \- code (1)
      \- link (1)
        " stat_density2d
    " .  If you have few unique x
    " values,
    \- code (1)
      \- link (1)
        " geom_boxplot
    " may also be useful.
    " Alternatively, you can summarise the number of points at
    " each location and display that in some way, using
    " 
    \- code (1)
      \- link (1)
        " stat_sum
    " . Another technique is to use
    " transparent points,
    \- code (1)
      > geom_point(alpha = 0.05)
    " .
  \- section (2)
    \-  (1)
      " Aesthetics
    \-  (8)
      " 
      " 
      \- code (1)
        > geom_point
      " understands the following aesthetics:
      " 
      " 
      \- itemize (34)
        " 
        \- item (0)
        " 
        \- code (1)
          > x
        " : horizontal position
        \- item (0)
        " 
        " 
        \- code (1)
          > y
        " : vertical position
        \- item (0)
        " 
        \- code (1)
          > shape
        " : point
        " shape.
        \- item (0)
        " 
        \- code (1)
          > colour
        " : point colour.
        \- item (0)
        " 
        " 
        \- code (1)
          > fill
        " : fill colour, only affects solid points
        \- item (0)
        " 
        " 
        \- code (1)
          > size
        " : size.
        \- item (0)
        " 
        \- code (1)
          > alpha
        " : alpha
        " transparency modifies colour.
      " 
  \- seealso (8)
    " 
    " 
    \- code (1)
      \- link (1)
        " scale_size
    " to see scale area of points,
    " instead of radius,
    \- code (1)
      \- link (1)
        " geom_jitter
    " to jitter
    " points to reduce (mild) overplotting
  \- examples (3)
    > 
    \- donttest (56)
      > 
      > p <- ggplot(mtcars, aes(wt, mpg))
      > p + geom_point()
      > 
      > # Add aesthetic mappings
      > p + geom_point(aes(colour = qsec))
      > p + geom_point(aes(alpha = qsec))
      > p + geom_point(aes(colour = factor(cyl)))
      > p + geom_point(aes(shape = factor(cyl)))
      > p + geom_point(aes(size = qsec))
      > 
      > # Change scales
      > p + geom_point(aes(colour = cyl)) + scale_colour_gradient(low
      > p + geom_point(aes(size = qsec)) + scale_area()
      > p + geom_point(aes(shape = factor(cyl))) + scale_shape(solid 
      > 
      > # Set aesthetics to fixed value
      > p + geom_point(colour = "red", size = 3)
      > qplot(wt, mpg, data = mtcars, colour = I("red"), size = I(3))
      > 
      > # Varying alpha is useful for large datasets
      > d <- ggplot(diamonds, aes(carat, price))
      > d + geom_point(alpha = 1/10)
      > d + geom_point(alpha = 1/20)
      > d + geom_point(alpha = 1/100)
      > 
      > # You can create interesting shapes by layering multiple poin
      > # different sizes
      > p <- ggplot(mtcars, aes(mpg, wt))
      > p + geom_point(colour="grey50", size = 4) + geom_point(aes(co
      > p + aes(shape = factor(cyl)) +
      > geom_point(aes(colour = factor(cyl)), size = 4) +
      > geom_point(colour="grey90", size = 1.5)
      > p + geom_point(colour="black", size = 4.5) +
      > geom_point(colour="pink", size = 4) +
      > geom_point(aes(shape = factor(cyl)))
      > 
      > # These extra layers don't usually appear in the legend, but 
      > # force their inclusion
      > p + geom_point(colour="black", size = 4.5, show_guide = TRUE)
      > geom_point(colour="pink", size = 4, show_guide = TRUE) +
      > geom_point(aes(shape = factor(cyl)))
      > 
      > # Transparent points:
      > qplot(mpg, wt, data = mtcars, size = I(5), alpha = I(0.2))
      > 
      > # geom_point warns when missing values have been dropped from
      > # and not plotted, you can turn this off by setting na.rm = T
      > mtcars2 <- transform(mtcars, mpg = ifelse(runif(32) < 0.2, NA
      > qplot(wt, mpg, data = mtcars2)
      > qplot(wt, mpg, data = mtcars2, na.rm = TRUE)
      > 
      > # Use qplot instead
      > qplot(wt, mpg, data = mtcars)
      > qplot(wt, mpg, data = mtcars, colour = factor(cyl))
      > qplot(wt, mpg, data = mtcars, colour = I("red"))
    >