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)

