How to Extract Data from a Multiple Column Table

Introduction

This article describes how to go from a multiple column table...

 

...to returning only the cells you need.

Requirements

A multiple-column table with a single statistic.

 

Method 1 - Point and click

1. Click on the Calculation equal sign.

2. Click on the page to insert a calculation box on the page.

3. While the cursor is blinking (active) in the R CODE box, click on a part of a table that you'd like to extract.

See Bespoke Analyses for examples and a demo of the feature.

 

Method 2 - By name

1. Select your table.

2. Copy the name from Properties > GENERAL > Name.

3. Select Calculation > Custom Code.

4. Go to Properties > R CODE in the object inspector.

5. Add a line in the format of table_name[row_name, column_name]

Using our example, the code to return just the second row of the Male column is:

table.age.gender["25 to 29","Male"]

And the results are:

To instead return values from the first three rows of the Male column is:

table.age.gender[c("18 to 24","25 to 29","30 to 34"),"Male"]

And the results are:

Leaving one of these arguments empty will return all the rows or columns respectively from the table. Below the Male argument has been removed from above so it returns both columns:

6. OPTIONAL: Add a percentage sign or adjust the number of decimal places via Properties > APPEARANCE > Number format.

 

Method 3 - By index

1. Select your table.

2. Copy the name from Properties > GENERAL > Name.

3. Select Calculation > Custom Code.

4. Go to Properties > R CODE in the object inspector.

5. Add a line in the format of table_name[row_index, column_index]

Using our example, the code to return the value from the second row of the first column is: table.age.gender[2,1]

And the results are:

To instead return values from the first three rows of the first column is: table.age.gender[c(1,2,3),1]

And the results are:

Alternatively, you can use index ranges: table.age.gender[1:3,1]

You can even reverse this to remove the other rows instead: table.age.gender[c(-4:-10,1)]

You can additionally remove the last row by using the NROW argument:

table.age.gender[-NROW(table.age.gender),]

And the results are:

6. OPTIONAL: Add a percentage sign or adjust the number of decimal places via Properties > APPEARANCE > Number format.

See also

How to Extract Data from a Single Column Summary Table

How to Extract Data from a Multiple Column Table with Multiple Statistics

How to Extract Data from a Multiple Column Table with Nested Data