plot.formula package:graphics R Documentation _F_o_r_m_u_l_a _N_o_t_a_t_i_o_n _f_o_r _S_c_a_t_t_e_r_p_l_o_t_s _D_e_s_c_r_i_p_t_i_o_n: Specify a scatterplot or add points or lines via a formula. _U_s_a_g_e: ## S3 method for class 'formula': plot(formula, data = parent.frame(), ..., subset, ylab = varnames[response], ask = dev.interactive()) ## S3 method for class 'formula': points(formula, data = parent.frame(), ..., subset) ## S3 method for class 'formula': lines(formula, data = parent.frame(), ..., subset) _A_r_g_u_m_e_n_t_s: formula: a 'formula', such as 'y ~ x'. data: a data.frame (or list) from which the variables in 'formula' should be taken. ...: Arguments to be passed to or from other methods. 'horizontal = TRUE' is also accepted. subset: an optional vector specifying a subset of observations to be used in the fitting process. ylab: the y label of the plot(s). ask: logical, see 'par'. _D_e_t_a_i_l_s: Both the terms in the formula and the '...' arguments are evaluated in 'data' enclosed in 'parent.frame()' if 'data' is a list or a data frame. The terms of the formula and those arguments in '...' that are of the same length as 'data' are subjected to the subsetting specified in 'subset'. If the formula in 'plot.formula' contains more than one non-response term, a series of plots of y against each term is given. A plot against the running index can be specified as 'plot(y ~ 1)'. Missing values are not considered in these methods, and in particular cases with missing values are not removed. If 'y' is an object (i.e. has a 'class' attribute) then 'plot.formula' looks for a plot method for that class first. Otherwise, the class of 'x' will determine the type of the plot. For factors this will be a parallel boxplot, and argument 'horizontal = TRUE' can be used (see 'boxplot'). _V_a_l_u_e: These functions are invoked for their side effect of drawing in the active graphics device. _S_e_e _A_l_s_o: 'plot.default', 'points', 'lines', 'plot.factor'. _E_x_a_m_p_l_e_s: op <- par(mfrow=c(2,1)) plot(Ozone ~ Wind, data = airquality, pch=as.character(Month)) plot(Ozone ~ Wind, data = airquality, pch=as.character(Month), subset = Month != 7) par(op)