Understanding Percentage Types

AddMaple provides three different ways to calculate percentages in pivot tables and charts. Each percentage type answers a different question about your data and helps you understand relationships from different perspectives.

Working with Percentages in AddMaple

Percentage Base Selection (Charts)

When viewing a pivot chart, you can choose which percentage base to display using the Percentage Base control in the left menu:

• Column A - Shows row percentages (how each row distributes across columns)
• Column B - Shows column percentages (how each column is composed of rows)
• All Rows - Shows sample percentages (percentage of the entire dataset)

This control appears when you switch from Count to Percentage mode in the chart menu.

Cell Tooltips (All Views)

When you hover over any cell in a chart or table, AddMaple shows a detailed tooltip that includes:

• The primary metric you've selected (count or percentage)
• All three percentage types (row, column, and sample percentages)
• The underlying counts and denominators
• Statistical significance indicators (when enabled)

This lets you quickly see the data from multiple perspectives without changing your view settings.

Column Visibility (Tables)

In pivot tables, you can customize which columns to display:

• Show or hide individual percentage columns (row %, column %, sample %)
• Show or hide count columns (results, rows, weighted values)
• Toggle statistical columns (z-scores, p-values)

Use the column visibility controls in the table header to customize your view.

The Three Percentage Types

Row Percentage (Column A Percent)

What it shows: The percentage of each row's total that falls into each column.

Calculation: (cell count ÷ row total) × 100

When to use: When you want to see how a specific group (row) distributes across different categories (columns).

Example: If you're looking at "Company vs Rating" data:

• Apple row: 36 people rated 1, 33 rated 2, etc.
• Row percentage shows: "Of all Apple respondents, 5.3% gave a rating of 1"
• All row percentages for Apple will add up to 100%

Column Percentage (Column B Percent)

What it shows: The percentage of each column's total that comes from each row.

Calculation: (cell count ÷ column total) × 100

When to use: When you want to see how each category (column) is composed across different groups (rows).

Example: In the same "Company vs Rating" data:

• Rating "1" column: 36 from Apple, 25 from Google
• Column percentage shows: "Of all people who rated 1, 59.0% were Apple users"
• All column percentages for rating "1" will add up to 100%

Sample Percentage

What it shows: The percentage of the entire sample that falls into each cell.

Calculation: (cell count ÷ total sample) × 100

When to use: When you want to see the overall distribution across your entire dataset.

Example: In the same data:

• Apple rating "1" cell: 36 people out of 2,371 total
• Sample percentage shows: "1.5% of all respondents were Apple users who rated 1"
• All sample percentages will add up to 100%

Visual Example

Here's how the same data looks with different percentage types:

When to Use Each Type

Use Row Percentages When:

• Comparing groups: "How do Apple users rate compared to Google users?"
• Understanding group behavior: "What percentage of Apple users gave each rating?"
• Identifying patterns within groups: "Do different companies have different rating distributions?"

Use Column Percentages When:

• Understanding category composition: "Who makes up each rating level?"
• Market share analysis: "What percentage of high ratings come from each company?"
• Identifying dominance: "Which company dominates the low ratings?"

Use Sample Percentages When:

• Overall distribution: "What's the general pattern across all respondents?"
• Market sizing: "What percentage of the total market does each segment represent?"
• Absolute impact: "How significant is each cell in the overall dataset?"

Row and Column Totals

Row Totals

• Count: Sum of all counts in the row
• Row %: Always 100% (by definition)
• Column %: Shows sample percentage (since column percentages don't sum meaningfully)
• Sample %: Sum of sample percentages in the row

Column Totals

• Count: Sum of all counts in the column
• Row %: Shows sample percentage (since row percentages don't sum meaningfully)
• Column %: Always 100% (by definition)
• Sample %: Sum of sample percentages in the column

Three-Way Tables

For three-way tables (e.g., Company × Rating × Gender), the percentage calculations work the same way, but with additional complexity. You can create three-way tables by adding multiple pivots or by grouping columns together.

• Row %: Percentage within each company-gender combination
• Column %: Percentage within each rating level
• Sample %: Percentage of the entire sample

The totals follow the same logic as two-way tables, with row totals showing sample percentages for column percentages and vice versa.

Practical Tips

• Use row percentages to compare groups
• Use column percentages to understand category composition
• Use sample percentages to see overall distribution
• Always show counts alongside percentages for context

Weighting and Percentages

When you apply a weight column to your data, AddMaple automatically adjusts all percentage calculations to reflect the weighted sample.

How Weighting Affects Calculations

Weighted vs Unweighted:

• Unweighted percentages: Based on raw response counts
• Weighted percentages: Based on weighted response counts that reflect your target population

Example with Weighting:

• Raw data: 100 Apple users, 200 Google users
• Weighted data: 150 Apple users, 150 Google users (after applying demographic weights)
• All percentages (row, column, sample) will be calculated using the weighted counts

Weighted Totals

When weighting is active, you'll see both unweighted and weighted totals in the status line:

• Unweighted: "Showing 1,431 results from 870 rows"
• Weighted: "Weighted: 1,520.5 results from 905.2 rows"

The percentage calculations use the weighted totals, ensuring your analysis reflects the true population distribution.

Multiselect Questions and Rows vs Results

Multiselect questions allow respondents to choose multiple options, which creates an important distinction between rows and results.

Understanding Rows vs Results

Rows (Respondents):

• Number of people who answered the question
• Each person counts as one row, regardless of how many options they selected

Results (Answers):

• Total number of individual selections made
• Each selected option counts as one result

Multiselect Example

If 100 people answer "Which brands do you use?" and can select multiple:

• 50 people select only "Apple"
• 30 people select both "Apple" and "Google"
• 20 people select only "Google"

Counts:

• Rows: 100 (number of respondents)
• Results: 150 (50 + 60 + 20 individual selections)

How This Affects Percentages

Row Percentages (Column A Percent):

• Based on the number of respondents in each row
• "Of all Apple users, what percentage selected each option?"

Column Percentages (Column B Percent):

• Based on the total number of times each option was selected
• "Of all 'Apple' selections, what percentage came from each user group?"

Sample Percentages (Sample Percent):

• Based on the total number of selections across all respondents
• "What percentage of all selections were 'Apple' from each group?"

Status Line with Multiselect

The status line shows both counts:

Showing 1,431 results from 870 rows

This tells you:

• 870 people answered the question (rows)
• They made 1,431 total selections (results)
• Results exceed rows because people could select multiple options

Hiding Multiselect Data

When you hide categories in multiselect data:

• Empty-like categories (EMPTY, ".") hide entire rows
• Other categories only hide the matching results, not the rows

Example status line:

Showing 1,411 results from 870 rows
20 results hidden
• None of the above — 20 results

This means 20 individual selections were hidden, but the 870 respondents still count toward the row base.

Key Points

• Row percentages show how each group distributes across categories
• Column percentages show how each category is composed across groups
• Sample percentages show the overall distribution in your dataset
• Each percentage type answers a different research question
• In charts, use the Percentage Base control to select which percentage to display
• Hover over any cell to see all three percentage types in the tooltip
• In tables, customize which percentage columns are visible
• Row and column totals use sample percentages when the other percentage type doesn't sum meaningfully
• Choose your percentage type based on what you want to learn from your data
• Weighting adjusts all calculations to reflect your target population
• Multiselect questions create a distinction between respondents (rows) and individual selections (results)
• Understanding rows vs results is crucial for interpreting multiselect data correctly