

_C_r_o_s_s _T_a_b_u_l_a_t_i_o_n

     table(..., exclude = c(NA, NaN))

_A_r_g_u_m_e_n_t_s:

     ...: objects which can be interpreted as factors
          (including character strings), or a list (or data
          frame) whose components can be so interpreted

 exclude: values to use in the exclude argument of `factor'
          when interpreting non-factor objects

_D_e_s_c_r_i_p_t_i_o_n:

     `table' uses the cross-classifying factors to build a
     contingency table of the counts at each combination of
     factor levels.

_E_x_a_m_p_l_e_s:

     ## Simple frequency distribution
     table(rpois(100,5))
     data(warpbreaks)
     attach(warpbreaks)
     ## Check the design:
     table(wool, tension)
     data(state)
     table(state.division, state.region)

     data(airquality)
     attach(airquality)
     # simple two-way contingency table
     table(cut(Temp, quantile(Temp)), Month)

