ggpcp                 package:ggplot                 R Documentation

_P_a_r_a_l_l_e_l _c_o_o_r_d_i_n_a_t_e_s _p_l_o_t.

_D_e_s_c_r_i_p_t_i_o_n:

     Generate a plot ``template'' for a paralell coordinates plot.

_U_s_a_g_e:

     ggpcp(data, vars=names(data), scale="range", ...)

_A_r_g_u_m_e_n_t_s:

    data: data frame

    vars: variables to include in parallel coordinates plot

   scale: scaling function, one of "range", "var" or "I"

     ...: other arguments passed on plot creation

_D_e_t_a_i_l_s:

     One way to think about a parallel coordinates plot, is as plotting
     the data after it has transformation been transformed to gain a
     new variable.  This function does this using 'melt'.

     This gives us enormous flexibility as we have separated out the
     type of drawing (lines by tradition) and can now use any of the
     existing grob functions.  In particular this makes it very easy to
     create parallel boxplots, as shown in the example.

_A_u_t_h_o_r(_s):

     Hadley Wickham <h.wickham@gmail.com>

_E_x_a_m_p_l_e_s:

     ggline(ggpcp(mtcars))
     ggline(ggpcp(mtcars, scale="var"))
     ggline(ggpcp(mtcars, vars=names(mtcars)[3:6], formula= . ~cyl, scale="I"))
     ggboxplot(ggpcp(mtcars, scale="I"))
     ggline(ggpcp(mtcars, vars=names(mtcars[2:6])))
     p <- ggpcp(mtcars, vars=names(mtcars[2:6]), formula=.~vs)
     ggline(p)
     ggline(p, aes=list(colour=mpg)) 

