Summarize and explore your data
Generate summary statistics for one or more variables in your data. The most powerful feature in Data > Explore is that you can easily describe the data by one or more other variables. Where the Data > Pivot tab works best for frequency tables and to summarize a single numeric variable, the Data > Explore tab allows you to summarize multiple variables at the same time using various statistics.
For example, if we select
price from the
diamonds dataset and click the
button we can see the number of observations (n), the mean, the
variance, etc. However, the mean price for each clarity level of the
diamond can also be easily provided by choosing
Group by variable.
Note that when a categorical variable (
factor) is selected from the
Numeric variable(s)dropdown menu it will be converted to a numeric variable if required for the selected function. If the factor levels are numeric these will be used in all calculations. Since the mean, standard deviation, etc. are not relevant for non-binary categorical variables, these will be converted to 0-1 (binary) variables where the first level is coded as 1 and all other levels as 0.
The created summary table can be stored in Radiant by clicking the
Store button. This can be useful if you want to create
plots of the summarized data in
> Visualize. To download the table to csv format
click the download icon on the top-right.
You can select options from
Column header dropdown to
switch between different column headers. Select either
Function (e.g., mean, median, etc),
(e.g., price, carat, etc), or the levels of the (first)
Group by variable (e.g., Fair-Ideal).
Below you will find a brief description of several functions
available from the
Apply function(s) dropdown menu. Most
functions, however, will be self-explanatory.
n calculates the number of observations, or rows, in
the data or in a group if a
Group by variable has been
n uses the
length function in
n_distinct calculates the number of distinct
n_missing calculates the number of missing values
cv is the coefficient of variation (i.e., mean(x) /
var calculate the sample standard
deviation and variance for numeric data
me calculates the margin of error for a numeric
variable using a 95% confidence level
prop calculates a proportion. For a variable with only
values 0 or 1 this is equivalent to
mean. For other numeric
variables it captures the occurrence of the maximum value. For a
factor it captures the occurrence of the first level.
varprop calculate the sample
standard deviation and variance for a proportion
meprop calculates the margin of error for a proportion
using a 95% confidence level
varpop calculate the population
standard deviation and variance
Filter data box to select (or omit) specific
sets of rows from the data. See the helpfile for
> View for details.
Add code to
> Rmd to (re)create the summary table by clicking the
icon on the bottom
left of your screen or by pressing
ALT-enter on your
For an overview of related R-functions used by Radiant to summarize and explore data see Data > Explore