# load sample date
data(efc)
# simple scatter plot, auto-jittering
sjp.scatter(efc$e16sex,efc$neg_c_7)
# simple scatter plot, no jittering needed
sjp.scatter(efc$c160age,efc$e17age)
# grouped scatter plot
sjp.scatter(efc$c160age,efc$e17age, efc$e42dep)
# grouped and jittered scatter plot with marginal rug plot
sjp.scatter(efc$e16sex,efc$neg_c_7, efc$c172code, showRug=TRUE)
# grouped and labelled scatter plot
sjp.scatter(efc$c160age,efc$e17age, efc$e42dep, title="Scatter Plot",
legendTitle = get_var_labels(efc)['e42dep'],
legendLabels = get_val_labels(efc)[['e42dep']],
axisTitle.x = get_var_labels(efc)['c160age'],
axisTitle.y = get_var_labels(efc)['e17age'],
showGroupFitLine = TRUE)
# grouped and labelled scatter plot as facets
sjp.scatter(efc$c160age,efc$e17age, efc$e42dep, title="Scatter Plot",
legendTitle = get_var_labels(efc)['e42dep'],
legendLabels = get_val_labels(efc)[['e42dep']],
axisTitle.x = get_var_labels(efc)['c160age'],
axisTitle.y = get_var_labels(efc)['e17age'],
showGroupFitLine = TRUE, facet.grid = TRUE, showSE = TRUE)
# plot residuals of fitted models
fit <- lm(neg_c_7 ~ quol_5, data = efc)
sjp.scatter(y = fit$residuals, showTotalFitLine = TRUE)
# -------------------------------
# auto-detection of labels
# -------------------------------
efc <- set_var_labels(efc, get_var_labels(efc))
# show axis titles
sjp.scatter(efc$c160age,efc$e17age, efc$e42dep)
# hide axis titles
sjp.scatter(efc$c160age,efc$e17age, efc$e42dep,
title="", axisTitle.x="", axisTitle.y="")
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