gghistogram              package:ggplot              R Documentation

_G_r_o_b _f_u_n_c_t_i_o_n: _h_i_s_t_o_g_r_a_m

_D_e_s_c_r_i_p_t_i_o_n:

     Draw a histogram

_U_s_a_g_e:

     gghistogram(plot = .PLOT, aesthetics=list(), ..., data=plot$data)

_A_r_g_u_m_e_n_t_s:

    plot: the plot object to modify

aesthetics: named list of aesthetic mappings, see details for more
          information

     ...: other options, see details for more information

    data: data source, if not specified the plot default will be used

_D_e_t_a_i_l_s:

     Aesthetic mappings that this grob function understands:

     Conceptually, the histogram is one of the most complicated of the
     grob functions, becuase it takes a 1D data set and makes it two
     dimensional.  This necessitates an extra step, the 'pre_histogram'
     function which bins the data and returns the bins with their
     counts. This data is then used my 'grob_histogram' to plot the
     points.

        *  x: x position (required)

     These can be specified in the plot defaults (see 'ggplot') or in
     the 'aesthetics' argument.  If you want to modify the position of
     the points or any axis options, you will need to add a position
     scale to the plot.  These functions start with 'ps', eg.
     'pscontinuous' or 'pscategorical'

     Other options:

        *  breaks: breaks argument passed to 'hist'

        *  scale: scale argument passed to 'hist'

_A_u_t_h_o_r(_s):

     Hadley Wickham <h.wickham@gmail.com>

_E_x_a_m_p_l_e_s:

     m <- ggplot(movies, aesthetics=list(x=rating))
     gghistogram(m)

