Plot Types

Plot Types

Six plot types of original ggplot2 are supported in ggplot2.sparkR now. More types will be updated.

Since the usage of ggplot2.sparkR is exactly the same with origin ggplot2.sparkR, we could click following links to reference them in the original ggplot2 documentation.

Geoms

Geoms, short for geometric objects, describe the type of plot you will produce.

• geom_bar
• geom_bin2d
• geom_boxplot
• geom_freqpoly
• geom_histogram

Statistics

It’s often useful to transform your data before plotting, and that’s what statistical transformations do.

• stat_bin
• stat_bin2d
• stat_boxplot
• stat_sum

Scales

• scale_x_log10
• scale_y_log10
• labs
• xlab
• ylab
• xlim
• ylim

Coordinate Systems

• coord_cartesian
• coord_flip

Facets

• facet_grid
• facet_null
• facet_wrap

Position Adjustment

• position_dodge
• position_fill
• position_stack

Examples

The parameter data in examples can be either R data.frame or Spark DataFrame.

If the input data is Spark DataFrame, heavyweight data processing stages are offloaded to the Spark backend using the SparkR API.

1. geom_bar

Bars, rectangles with bases on x-axis

ggplot(data, aes(x = Item, fill = Payment)) + geom_bar()

2. geom_histogram

Histogram. Bars, rectangles with bases on x-axis using continuous data.

ggplot(data, aes(x = Price)) + geom_histogram(binwidth = 10)

3. stat_sum

Sum unique values. Useful for overplotting on scatterplots.

ggplot(data, aes(x = Item, y = Payment)) + stat_sum()

4. geom_bin2d

Add heatmap of 2d bin counts.

ggplot(data, aes(x = Item, y = Price)) + geom_bin2d()

5. geom_boxplot

Calculate components of box and whisker plot.

ggplot(data, aes(x = Item, y = Price)) + geom_boxplot()