What package has ggplot2?

You can view the ggplot2 page for more information. Although it’s fairly common practice to simply refer to the package as ggplot, it is, in fact, the second implementation of the grammar of graphics for R; hence, the package is ggplot2. As of this writing, the current version of the package is version 0.9.

What can I do with ggplot2?

ggplot2 is the most popular data visualization package in the R community. It was created by Hadley Wickham in 2005. It was implemented based on Leland Wilkinson’s Grammar of Graphics — a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers.

What is a ggplot2 aesthetic?

In ggplot2 , aesthetic means “something you can see”. Each aesthetic is a mapping between a visual cue and a variable. Examples include: position (i.e., on the x and y axes) color (“outside” color)

What is a ggplot2 object?

In a ggplot object, layers reside in a list, and their positions in the list determine the plotting order when generating the graphical output. The grammar of graphics treats the list of layers as a stack using only push operations. The table below list the names and purpose of these functions.

What is the latest version of ggplot2?

ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics

What library is needed for ggplot?

The ggplot2 package can be easily installed using the R function install. packages() . The above code will automatically download the ggplot2 package, from the CRAN (Comprehensive R Archive Network) repository, and install it.

Can I use ggplot in Python?

Using ggplot in Python allows you to build visualizations incrementally, first focusing on your data and then adding and tuning components to improve its graphical representation. In the next section, you’ll learn how to use colors and how to export your visualizations.

Is ggplot2 a package in R?

ggplot2 is a R package dedicated to data visualization. It can greatly improve the quality and aesthetics of your graphics, and will make you much more efficient in creating them.

What is a geom?

Geometric objects (geoms) are the visual representations of (subsets of) observations.

What does AES mean in R?

aesthetic mappings
aes: Construct aesthetic mappings Aesthetic mappings describe how variables in the data are mapped to visual properties (aesthetics) of geoms.

What is AES function in R?

Description. aes creates a list of unevaluated expressions. This function also performs partial name matching, converts color to colour, and old style R names to ggplot names (eg. pch to shape, cex to size)

Is there a ggplot1?

ggplot1 is an update of ggplot, the package that preceded ggplot2. ggplot1 is mostly made available out of historical interest, to illustrate how my thinking about API design in R has evolved over the years.

How to see plot theme options in ggplot2?

Update If you would like to see the options that are in use on a current plot, you can use plot_theme (x) to see all of the options that are currently set for the plot named x. It will not be a comprehensive list, but should help if you want to change something like the font size for an axis label.

Which is the best ggplot2 chart to use?

Ranking 1 Ordered Bar Chart. Ordered Bar Chart is a Bar Chart that is ordered by the Y axis variable. 2 Lollipop Chart. Lollipop charts conveys the same information as in bar charts. 3 Dot Plot. Dot plots are very similar to lollipops, but without the line and is flipped to horizontal position. 4 Slope Chart. 5 Dumbbell Plot.

How to create a ggplot2 plot using ggsave ( )?

All ggplot2 plots begin with a call to ggplot(), supplying default data and aesthethic mappings, specified by aes(). You then add layers, scales, coords and facets with +. To save a plot to disk, use ggsave(). ggplot() Create a new ggplot.

How to create a reference line in ggplot?

There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot (). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify () for which variables will be created.