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

Introduction

This article describes how to go from a multiple column table with more than one statistic...

...to returning only the cells you need.

Requirements

A multiple-column table with multiple statistics.

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, statistic_name]

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

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

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

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

Leaving one of these arguments empty will return all the rows, columns, or statistics 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, statistic_index]

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

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

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

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

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

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

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

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