table                  package:base                  R Documentation

_C_r_o_s_s _T_a_b_u_l_a_t_i_o_n

_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.

_U_s_a_g_e:

     table(..., exclude = c(NA, NaN), dnn, deparse.level = 1)

_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

     dnn: the names to be given to the dimensions in the result (`the
          dimname names'

deparse.level: controls how the default `dnn' is constructed. See
          details.

_D_e_t_a_i_l_s:

     If the argument `dnn' is not supplied, the internal function
     `list.names' is called to compute the `dimname names'. If the
     arguments in `...' are named, those names are used. For the
     remaining arguments, `deparse.level = 0' gives an empty name,
     `deparse.level = 1' uses the supplied argument if it is a symbol,
     and `deparse.level = 2' will deparse the argument.

_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)

     a <- letters[1:3]
     table(a, sample(a)) # dnn is  c("a", "")
     table(a, sample(a), deparse.level = 0) # dnn is  c("", "")
     table(a, sample(a), deparse.level = 2) # dnn is  c("a", "sample(a)")

