Summarize and explore your data
Generate summary statistics for one or more variables in your data. The most powerful feature in Explore is that you can easy describe the data by one or more other variables. Where the Pivot tab works best for frequency tables and to summarize a single numerical variable, the 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 we can see the number of observations (n), the mean, the median, etc. etc. However, the mean price for each clarity level of the diamond can also be easily provided by choosing
clarity as the Group by variable.
The created summary table can be stored in Radiant by clicking the
Store button. This can be useful if you want to create plots using the summarized data. To download the table to csv format click the download icon on the top-right.
You can select options from
Column variable dropdown to switch between different column headers. Select either the
functions (e.g., mean, median, etc), the variables (e.g., price, carat, etc), or the levels of the (first)
Group by variable (e.g., Fair-Ideal).
n determines the number of observations, or rows, in the data or in a group if a
group_by variable has been selected (
n uses the
length function in R)
n_distinct determines the number of distinct values in a variable
n_missing determines the number of missing values in a variable
cv is the coefficient of variation (i.e., mean(x) / sd(x))
var calculate the sample standard deviation and variance
varp calculate the population standard deviation and variance
Filter box to select (or omit) specific sets of rows from the data. See the helpfile for Data > View for details.
For larger datasets it can useful to click
Pause explore before selecting categorical and numerical variables, entering filters, etc. When you are ready to generate the explore table make sure that
Pause explore is not checked. When
Pause explore is not checked, any changes to the inputs will automatically result in a new table.
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