Introduction
This article describes how to go from a single column table...
...to returning only the cells you need.
Requirements
A single-column summary table.
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 table 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]
Using our example, the code to return values from just the second row is: table.age["25 to 29"]
To instead return values from the first three rows the code is: table.age[c("18 to 24","25 to 29","30 to 34")]
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 table 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[index_number]
Using our example, the code to return the value from the second row is: table.age[2]
To instead return values from the first three rows the code is: table.age[c(1,2,3)]
Alternatively, you can use index ranges. The code to return the first three values is: table.age[1:3]
You can even reverse this and remove the other rows instead:table.age[c(-4:-10)]
You can additionally remove the last row by using the NROW argument:
table.age[-NROW(table.age)]
6. OPTIONAL: Add a percentage sign or adjust the number of decimal places via Properties > APPEARANCE > Number format.
Notes
You can retain the % column header (or whatever the column name is in your SUMMARY table with the following code where table.age is your single column table. See How to Relabel Rows and Columns in an R Table for more detail.
x=data.frame(table.age[-NROW(table.age)])
colnames(x)=attr(table.age,"statistic")
x

See also
How to Extract Data from a Multiple Column 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