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Graphs

Start with the expanded example for each command. Open the variants for options and alternative R approaches. Read the qualifications before adapting the code.

binscatter

Binned scatter plot

Stata

binscatter y x

R Package:binsreg

binsreg::binsreg(y, x, data = data)

Differs from Stata statar::stat_binmean() adds binned means to a ggplot: ggplot(data, aes(x, y)) + statar::stat_binmean(n = 20). binsreg() defaults to data-driven bin selection and inference; binscatter defaults to fixed quantile bins and an OLS fit. Match bins and fit settings explicitly.

Stata reference · R reference

coefplot

Coefficient plot

Stata

coefplot

R Package:modelsummary

modelsummary::modelplot(fit)

Stata reference · R reference

dotplot

Show individual observations by category

Stata

dotplot y, over(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(group, y)) + ggplot2::geom_point(position = ggplot2::position_jitter(width = 0.15, height = 0))

Differs from Stata This uses horizontally jittered observations rather than Stata dot-stacking rules.

Stata reference · R reference

graph

Bar chart of counts

Stata

graph bar (count), over(x)

R Package:ggplot2

ggplot(data, aes(x)) + geom_bar()

Stata reference · R reference

Bar chart of group means

Stata

graph bar (mean) y, over(group)

R Package:ggplot2

ggplot(data, aes(group, y)) + stat_summary(fun = mean, geom = "bar")

Stata reference · R reference

Box plot

Stata

graph box y, over(group)

R Package:ggplot2

ggplot(data, aes(group, y)) + geom_boxplot()

Differs from Stata ggplot2 boxplot hinges use R quantile rules; Stata uses Stata percentiles, which may differ in small samples and with ties.

Stata reference · R reference

Save the last graph

Stata

graph export figure.png

R Package:ggplot2

ggsave("figure.png")

Stata reference · R reference

Pie chart

Stata

graph pie, over(group)

R Package:ggplot2

ggplot(data, aes(x = "", fill = group)) + geom_bar() + coord_polar(theta = "y")

Stata reference · R reference

16 more examples and alternatives

Combine plots

Stata

graph combine g1.gph g2.gph

R Package:patchwork

patchwork::wrap_plots(p1, p2)

With patchwork attached, p1 + p2 does the same.

Stata reference · R reference

Dot chart

Stata

graph dot (mean) y, over(group)

R Package:ggplot2

ggplot(data, aes(y, group)) + stat_summary(fun = mean, geom = "point")

Stata reference · R reference

Horizontal bar chart

Stata

graph hbar (mean) y, over(group)

R Package:ggplot2

ggplot(data, aes(group, y)) + stat_summary(fun = mean, geom = "bar") + coord_flip()

Stata reference · R reference

Horizontal box plot

Stata

graph hbox y, over(group)

R Package:ggplot2

ggplot(data, aes(y, group)) + geom_boxplot()

Differs from Stata ggplot2 boxplot hinges use R quantile rules; Stata uses Stata percentiles, which may differ in small samples and with ties.

Stata reference · R reference

Scatter-plot matrix

Stata

graph matrix x1 x2 x3

R Package:graphics

pairs(select(data, x1, x2, x3))

GGally::ggpairs() draws a ggplot2 version.

Stata reference · R reference

Save a plot to edit later

Stata

graph save fig.gph

R Package:base

saveRDS(p, "fig.rds")

Stata reference · R reference

Plot group frequencies

Stata

graph bar (count), over(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(group)) + ggplot2::geom_bar()

Differs from Stata Reproduces the displayed count, percent or summary layer, rather than Stata graph display defaults. Match category order and missingness; ggplot themes, axis scales and bar annotations follow R conventions.

Stata reference · R reference

Plot group means as bars

Stata

graph bar (mean) y, over(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(group, y)) + ggplot2::stat_summary(fun = mean, geom = "col")

Differs from Stata Reproduces the displayed count, percent or summary layer, rather than Stata graph display defaults. Match category order and missingness; ggplot themes, axis scales and bar annotations follow R conventions.

Stata reference · R reference

Label summary bars with their values

Stata

graph bar (mean) y, over(group) blabel(bar)

R Package:ggplot2

{ plot_data <- aggregate(y ~ group, data, mean); ggplot2::ggplot(plot_data, ggplot2::aes(group, y)) + ggplot2::geom_col() + ggplot2::geom_text(ggplot2::aes(label = round(y, 1)), vjust = -0.3) }

Differs from Stata Reproduces the displayed count, percent or summary layer, rather than Stata graph display defaults. Match category order and missingness; ggplot themes, axis scales and bar annotations follow R conventions.

Stata reference · R reference

Plot group medians as bars

Stata

graph bar (median) y, over(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(group, y)) + ggplot2::stat_summary(fun = median, geom = "col")

Differs from Stata Reproduces the displayed count, percent or summary layer, rather than Stata graph display defaults. Match category order and missingness; ggplot themes, axis scales and bar annotations follow R conventions.

Stata reference · R reference

Plot group percentages

Stata

graph bar (percent), over(group)

R Package:ggplot2

{ counts <- as.data.frame(table(data$group)); ggplot2::ggplot(counts, ggplot2::aes(Var1, Freq / sum(Freq) * 100)) + ggplot2::geom_col() }

Differs from Stata Reproduces the displayed count, percent or summary layer, rather than Stata graph display defaults. Match category order and missingness; ggplot themes, axis scales and bar annotations follow R conventions.

Stata reference · R reference

Plot group totals as bars

Stata

graph bar (sum) y, over(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(group, y)) + ggplot2::stat_summary(fun = sum, geom = "col")

Differs from Stata Reproduces the displayed count, percent or summary layer, rather than Stata graph display defaults. Match category order and missingness; ggplot themes, axis scales and bar annotations follow R conventions.

Stata reference · R reference

Compare distributions with box plots

Stata

graph box y, over(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(group, y)) + ggplot2::geom_boxplot()

Differs from Stata Box-plot hinges and whisker defaults should be checked when numerical parity is required.

Stata reference · R reference

Hide box-plot outlier markers

Stata

graph box y, over(group) nooutsides

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(group, y)) + ggplot2::geom_boxplot(outlier.shape = NA)

Differs from Stata Box-plot hinges and whisker defaults should be checked when numerical parity is required.

Stata reference · R reference

Plot group means as dots

Stata

graph dot (mean) y, over(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y, group)) + ggplot2::stat_summary(fun = mean, geom = "point")

Differs from Stata Reproduces the displayed count, percent or summary layer, rather than Stata graph display defaults. Match category order and missingness; ggplot themes, axis scales and bar annotations follow R conventions.

Stata reference · R reference

Draw horizontal box plots

Stata

graph hbox y, over(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y, group)) + ggplot2::geom_boxplot()

Differs from Stata Box-plot hinges and whisker defaults should be checked when numerical parity is required.

Stata reference · R reference

heatplot

Heat map of the mean of z over binned x and y

Stata

heatplot z y x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y, z = z)) + ggplot2::stat_summary_2d(fun = mean)

Differs from Stata Community command. Both average z within cells, but bin counts and boundaries differ; set bins explicitly (bins() in Stata, bins = in R) when comparing. Colour ramps follow each program’s defaults.

Stata reference · R reference

1 more examples and alternatives

Heat map of the mean of z over categories of x and y

Stata

heatplot z i.y i.x

R Package:ggplot2

ggplot2::ggplot(stats::aggregate(z ~ x + y, data = data, FUN = mean), ggplot2::aes(factor(x), factor(y), fill = z)) + ggplot2::geom_tile()

Differs from Stata Community command. One tile per observed x-y combination, filled with the mean of z; empty combinations are left blank in both.

Stata reference · R reference

histogram

Histogram

Stata

histogram x

R Package:ggplot2

ggplot(data, aes(x)) + geom_histogram()

Differs from Stata geom_histogram() defaults to counts and 30 bins; Stata histogram defaults to density with a different bin rule. Specify breaks/binwidth and the y statistic.

Stata reference · R reference

6 more examples and alternatives

Compare histograms across groups

Stata

histogram y, by(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y)) + ggplot2::geom_histogram(bins = 10) + ggplot2::facet_wrap(~group)

Differs from Stata Set boundaries and interval closure explicitly when matching Stata bin counts.

Stata reference · R reference

Histogram on the density scale

Stata

histogram y, density

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y, ggplot2::after_stat(density))) + ggplot2::geom_histogram(bins = 10)

Differs from Stata Set boundaries and interval closure explicitly when matching Stata bin counts.

Stata reference · R reference

Histogram on the frequency scale

Stata

histogram y, frequency

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y)) + ggplot2::geom_histogram(bins = 10)

Differs from Stata Set boundaries and interval closure explicitly when matching Stata bin counts.

Stata reference · R reference

Histogram on the percentage scale

Stata

histogram y, percent

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y, ggplot2::after_stat(count / sum(count) * 100))) + ggplot2::geom_histogram(bins = 10)

Differs from Stata Set boundaries and interval closure explicitly when matching Stata bin counts.

Stata reference · R reference

Choose histogram width and boundary

Stata

histogram y, width(2) start(0)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y)) + ggplot2::geom_histogram(binwidth = 2, boundary = 0)

Differs from Stata Set boundaries and interval closure explicitly when matching Stata bin counts.

Stata reference · R reference

Histogram for integer-valued observations

Stata

histogram z, discrete

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(z)) + ggplot2::geom_histogram(binwidth = 1, boundary = 0.5)

Differs from Stata Set boundaries and interval closure explicitly when matching Stata bin counts.

Stata reference · R reference

kdensity

Density plot

Stata

kdensity x

R Package:ggplot2

ggplot(data, aes(x)) + geom_density()

Differs from Stata Default kernel-density bandwidth rules differ; specify kernel, bandwidth and evaluation range before comparing curves.

Stata reference · R reference

4 more examples and alternatives

Plot a kernel density estimate

Stata

kdensity y

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y)) + ggplot2::geom_density()

Differs from Stata R and Stata bandwidth rules and local smoothing algorithms can differ; this is a graphical alternative, not an exact numerical replication.

Stata reference · R reference

Estimate a density for a subgroup

Stata

kdensity y if group == "A"

R Package:ggplot2

ggplot2::ggplot(subset(data, group == "A"), ggplot2::aes(y)) + ggplot2::geom_density()

Differs from Stata R and Stata bandwidth rules and local smoothing algorithms can differ; this is a graphical alternative, not an exact numerical replication.

Stata reference · R reference

Specify a kernel bandwidth

Stata

kdensity y, bwidth(1)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y)) + ggplot2::geom_density(bw = 1)

Differs from Stata R and Stata bandwidth rules and local smoothing algorithms can differ; this is a graphical alternative, not an exact numerical replication.

Stata reference · R reference

Use a Gaussian density kernel

Stata

kdensity y, kernel(gaussian)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(y)) + ggplot2::geom_density(kernel = "gaussian")

Differs from Stata R and Stata bandwidth rules and local smoothing algorithms can differ; this is a graphical alternative, not an exact numerical replication.

Stata reference · R reference

line

Line plot

Stata

line y x

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_line()

Differs from Stata geom_line() sorts by x within groups; Stata line/connected uses observation order without the sort option.

Stata reference · R reference

3 more examples and alternatives

Line plot sorted by the horizontal variable

Stata

line y x, sort

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_line()

Differs from Stata Maps the stated axes and layer; line sorts by x in ggplot while Stata uses sort here. Plot themes, axis expansion, missing-point warnings and facet scales follow R defaults.

Stata reference · R reference

Draw line plots in separate group panels

Stata

line y x, sort by(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_line() + ggplot2::facet_wrap(~group)

Differs from Stata Maps the stated axes and layer; line sorts by x in ggplot while Stata uses sort here. Plot themes, axis expansion, missing-point warnings and facet scales follow R defaults.

Stata reference · R reference

Set a line colour

Stata

line y x, sort lcolor(red)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_line(colour = "red")

Differs from Stata Maps the stated axes and layer; line sorts by x in ggplot while Stata uses sort here. Plot themes, axis expansion, missing-point warnings and facet scales follow R defaults.

Stata reference · R reference

lowess

Smoothed scatter plot

Stata

lowess y x

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_point() + geom_smooth(method = "loess")

Differs from Stata LOESS local polynomials differ from Stata LOWESS smoothing, robustness iterations and bandwidth defaults; the fitted curves need not coincide.

Stata reference · R reference

1 more examples and alternatives

Draw a local regression smooth

Stata

lowess y x, bwidth(0.5)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_smooth(method = "loess", formula = y ~ x, span = 0.5, se = FALSE)

Differs from Stata R and Stata bandwidth rules and local smoothing algorithms can differ; this is a graphical alternative, not an exact numerical replication.

Stata reference · R reference

pchi

Compare empirical and chi-squared probabilities

Stata

pchi y, df(2)

R Package:graphics

graphics::plot(ppoints(length(data$y)), pchisq(sort(data$y), df = 2))

Differs from Stata A diagnostic plotting workflow; plotting-position and standardization defaults can differ from Stata.

Stata reference · R reference

pnorm

Assess a standardized normal P-P relationship

Stata

pnorm y

R Package:graphics

graphics::plot(ppoints(length(data$y)), pnorm(as.numeric(scale(sort(data$y)))), xlab = "Empirical", ylab = "Normal")

Differs from Stata A diagnostic plotting workflow; plotting-position and standardization defaults can differ from Stata.

Stata reference · R reference

qchi

Compare sample quantiles with chi-squared quantiles

Stata

qchi y, df(2)

R Package:graphics

graphics::plot(qchisq(ppoints(length(data$y)), df = 2), sort(data$y))

Differs from Stata A diagnostic plotting workflow; plotting-position and standardization defaults can differ from Stata.

Stata reference · R reference

qnorm

Normal quantile plot

Stata

qnorm x

R Package:ggplot2

ggplot(data, aes(sample = x)) + geom_qq() + geom_qq_line()

Differs from Stata geom_qq() defaults to theoretical standard-normal quantiles; qnorm scales the normal axis by the sample mean and SD. Match axis scaling to compare points.

Stata reference · R reference

qqplot

Compare two empirical distributions with a Q-Q plot

Stata

qqplot y x

R Package:stats

stats::qqplot(data$x, data$y)

Differs from Stata A diagnostic plotting workflow; plotting-position and standardization defaults can differ from Stata.

Stata reference · R reference

quantile

Plot ordered data against cumulative fractions

Stata

quantile y

R Package:graphics

graphics::plot(ppoints(sum(!is.na(data$y))), sort(data$y), xlab = "Fraction", ylab = "y")

Differs from Stata A diagnostic plotting workflow; plotting-position and standardization defaults can differ from Stata.

Stata reference · R reference

scatter

Scatter plot

Stata

scatter y x

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_point()

Stata reference · R reference

23 more examples and alternatives

Label the points

Stata

scatter y x, mlabel(name)

R Package:ggplot2

ggplot(data, aes(x, y, label = name)) + geom_point() + geom_text()

Stata reference · R reference

Add a reference line

Stata

scatter y x, xline(0)

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_point() + geom_vline(xintercept = 0)

geom_hline(yintercept = 0) is yline().

Stata reference · R reference

Scatter plot with ggplot2

Stata

scatter y x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point()

Differs from Stata Maps the stated axes and layer; line sorts by x in ggplot while Stata uses sort here. Plot themes, axis expansion, missing-point warnings and facet scales follow R defaults.

Stata reference · R reference

Make the plotting panel square

Stata

scatter y x, aspectratio(1)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::theme(aspect.ratio = 1)

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Separate scatter plots by group

Stata

scatter y x, by(group)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::facet_wrap(~group)

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Jitter overlapping observations

Stata

scatter y x, jitter(2)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_jitter(width = 0.2, height = 0.2)

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Hide a graph legend

Stata

scatter y x, legend(off)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point(ggplot2::aes(colour = group)) + ggplot2::theme(legend.position = "none")

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Set the marker colour

Stata

scatter y x, mcolor(red)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point(colour = "red")

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Label each point with a variable

Stata

scatter y x, mlabel(label)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_text(ggplot2::aes(label = label))

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Increase marker size

Stata

scatter y x, msize(large)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point(size = 3)

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Draw hollow circular markers

Stata

scatter y x, msymbol(Oh)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point(shape = 1)

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Add a source note to a graph

Stata

scatter y x, note("Source: survey")

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::labs(caption = "Source: survey")

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Use a monochrome-friendly theme

Stata

scatter y x, scheme(s2mono)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::theme_bw()

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Add a graph subtitle

Stata

scatter y x, subtitle("Wave 1")

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::labs(subtitle = "Wave 1")

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Add a graph title

Stata

scatter y x, title("Sample")

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::labs(title = "Sample")

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Choose horizontal axis breaks

Stata

scatter y x, xlabel(0(5)30)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::scale_x_continuous(breaks = seq(0, 30, 5))

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Add a vertical reference line

Stata

scatter y x, xline(10)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::geom_vline(xintercept = 10)

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Use a logarithmic predictor axis

Stata

scatter y x, xscale(log)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::scale_x_log10()

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Label the horizontal axis

Stata

scatter y x, xtitle("Age")

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::labs(x = "Age")

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Choose vertical axis breaks

Stata

scatter y x, ylabel(0(5)20)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::scale_y_continuous(breaks = seq(0, 20, 5))

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Add a horizontal reference line

Stata

scatter y x, yline(5)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::geom_hline(yintercept = 5)

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Use a logarithmic response axis

Stata

scatter y x, yscale(log)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::scale_y_log10()

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

Label the vertical axis

Stata

scatter y x, ytitle("Income")

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::labs(y = "Income")

Differs from Stata The R example implements the graphical intent; size, jitter and theme scales are not numerically identical to Stata.

Stata reference · R reference

serrbar

Plot supplied estimates and standard errors

Stata

serrbar y se x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_errorbar(ggplot2::aes(ymin = y - se, ymax = y + se)) + ggplot2::geom_point()

Differs from Stata Here se is a supplied standard-error variable; Stata serrbar defaults to one standard error. Rename the variable to suit your data.

Stata reference · R reference

set

Change the look of every graph

Stata

set scheme s1mono

R Package:ggplot2

theme_set(theme_bw())

Stata reference · R reference

spikeplot

Plot spikes for the frequencies of distinct values

Stata

spikeplot z

R Package:graphics

{ counts <- as.data.frame(table(data$z)); graphics::plot(as.numeric(as.character(counts$Var1)), counts$Freq, type = "h") }

Differs from Stata Draws one spike for each observed value with its count. Axis ticks, spike widths, handling of missing values and graphics device styling differ from Stata spikeplot.

Stata reference · R reference

symplot

Check symmetry around the sample median

Stata

symplot y

R Package:graphics

{ values <- sort(data$y); half <- length(values) %/% 2L; centre <- median(values); graphics::plot(centre - rev(head(values, half)), tail(values, half) - centre) }

Differs from Stata A diagnostic plotting workflow; plotting-position and standardization defaults can differ from Stata.

Stata reference · R reference

twoway

Scatter plot with a fitted line

Stata

twoway (scatter y x) (lfit y x)

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_point() + geom_smooth(method = "lm")

Differs from Stata geom_smooth(method = “lm”) adds a confidence band by default; lfit has no band. Use se = FALSE for the same plotted layer.

Stata reference · R reference

Area plot

Stata

twoway area y x

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_area()

Stata reference · R reference

Connected line plot

Stata

twoway connected y x

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_line() + geom_point()

Differs from Stata geom_line() sorts by x within groups; Stata line/connected uses observation order without the sort option.

Stata reference · R reference

Shaded range

Stata

twoway rarea hi lo x

R Package:ggplot2

ggplot(data, aes(x, ymin = lo, ymax = hi)) + geom_ribbon()

Stata reference · R reference

Range plot with capped spikes

Stata

twoway rcap hi lo x

R Package:ggplot2

ggplot(data, aes(x, ymin = lo, ymax = hi)) + geom_errorbar()

Stata reference · R reference

20 more examples and alternatives

Colour points by group

Stata

twoway (scatter y x if g == 1) (scatter y x if g == 2)

R Package:ggplot2

ggplot(data, aes(x, y, colour = factor(g))) + geom_point()

Stata reference · R reference

Linear fit with a confidence band

Stata

twoway lfitci y x

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_smooth(method = "lm")

Stata reference · R reference

Quadratic fit

Stata

twoway qfit y x

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_smooth(method = "lm", formula = y ~ poly(x, 2), se = FALSE)

Stata reference · R reference

One panel per group

Stata

twoway scatter y x, by(group)

R Package:ggplot2

ggplot(data, aes(x, y)) + geom_point() + facet_wrap(~group)

Stata reference · R reference

Overlay a linear fitted relationship

Stata

twoway (scatter y x) (lfit y x)

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point() + ggplot2::geom_smooth(method = "lm", formula = y ~ x, se = FALSE)

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Fill the area beneath a line

Stata

twoway area y x, sort

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_area()

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Connect points in horizontal order

Stata

twoway connected y x, sort

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_line() + ggplot2::geom_point()

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Draw contour lines on a regular grid

Stata

twoway contour y x z

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_contour(ggplot2::aes(z = z))

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Draw points with drop lines

Stata

twoway dropline y x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_segment(ggplot2::aes(xend = x, yend = 0)) + ggplot2::geom_point()

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Plot a linear fit with confidence limits

Stata

twoway lfitci y x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_smooth(method = "lm", formula = y ~ x, level = 0.95)

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Draw arrows between paired coordinates

Stata

twoway pcarrow y x hi z

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_segment(ggplot2::aes(xend = z, yend = hi), arrow = grid::arrow())

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Connect paired coordinate endpoints

Stata

twoway pcspike y x hi z

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_segment(ggplot2::aes(xend = z, yend = hi))

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Plot a quadratic fit with confidence limits

Stata

twoway qfitci y x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_smooth(method = "lm", formula = y ~ poly(x, 2), level = 0.95)

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Draw a shaded uncertainty band

Stata

twoway rarea lo hi x, sort

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_ribbon(ggplot2::aes(ymin = lo, ymax = hi))

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Draw bars spanning lower and upper values

Stata

twoway rbar lo hi x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_rect(ggplot2::aes(xmin = x - 0.4, xmax = x + 0.4, ymin = lo, ymax = hi))

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Draw capped uncertainty intervals

Stata

twoway rcap lo hi x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_errorbar(ggplot2::aes(ymin = lo, ymax = hi))

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Plot both endpoints of a range

Stata

twoway rscatter lo hi x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point(ggplot2::aes(y = lo)) + ggplot2::geom_point(ggplot2::aes(y = hi))

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Show ranges with vertical lines

Stata

twoway rspike lo hi x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_linerange(ggplot2::aes(ymin = lo, ymax = hi))

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Draw a two-variable scatter plot

Stata

twoway scatter y x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_point()

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

Draw vertical spikes from zero

Stata

twoway spike y x

R Package:ggplot2

ggplot2::ggplot(data, ggplot2::aes(x, y)) + ggplot2::geom_segment(ggplot2::aes(xend = x, yend = 0))

Differs from Stata Graphical workflow; plotting defaults can differ.

Stata reference · R reference

vioplot

Violin plot

Stata

vioplot y, over(group)

R Package:ggplot2

ggplot(data, aes(group, y)) + geom_violin()

Stata reference · R reference