# R Commander – data manipulation and summaries

**Software for Exploratory Data Analysis and Statistical Modelling**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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Previously we considered the R Commander interface as a simple GUI for the R statistical software system. Here we will look at how to undertake data manipulation and creating basic statistical summaries of data sets.

Fast Tube by Casper

The R Commander GUI has two menus **“Data”** and **“Statistics”** that are used for manipulating data sets and calculating descriptive statistics and various commonly used statistical techniques. In the **“Data”** menu there is a sub-menu **“Manage variables in active data set”** that has some useful features. These include:

- Compute new variables – used for transforming variables, e.g. converting to a logarithmic scale.
- Standardise variables – centre data on the mean and scale to the variance of the variable.
- Convert numeric variables to factors – this is useful for categorical data that is recorded as numbers where we would be interested in working with these as factor levels rather than the actual values.
- Bin numeric variable – in some situations converting a continuous measurement to groups can make exploratory analysis easier.

The **“Statistics”** menu provides access to various descriptive and summary statistics via the **“Summaries”** sub-menu including:

- Numerical summaries – mean, standard deviation or quantiles for a variable.
- Frequency distributions – used to create tables to summarise the number of times each level of a factor occurs in a variable.
- Table of statistics – mean, standard deviation for a numeric variable for each of the groups within a categorical variable.
- Correlation matrix – the correlation between a set of numeric variables in a data frame.

There are other data manipulation options and summary functions available from these two menus.

Other useful resources are provided on the Supplementary Material page.

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**Software for Exploratory Data Analysis and Statistical Modelling**.

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