Appending queries in Excel - Deep Dive

Overview - Appending queries

What is it?

Appending queries means combining data from two or more tables or lists by stacking them one after another. Instead of joining columns side-by-side, you add rows from one table below the rows of another. This helps when you have similar data split across different sheets or files and want to see it all together in one place.

Why it matters

Without appending queries, you would have to manually copy and paste data from different sources, which is slow and error-prone. Appending lets you automatically combine data, saving time and reducing mistakes. It makes data analysis easier because you can work with one complete dataset instead of many scattered pieces.

Where it fits

Before learning appending queries, you should understand basic Excel tables and how to load data into Power Query. After mastering appending, you can learn about merging queries, filtering data, and creating advanced reports.

Mental Model

Core Idea

Appending queries stacks tables vertically by adding rows from one table below another to create one combined list.

Think of it like...

Appending queries is like stacking pancakes: each pancake is a table, and stacking them creates one tall stack to eat all at once.

Table A       Table B
┌───────┐     ┌───────┐
│ Row 1 │     │ Row 1 │
│ Row 2 │     │ Row 2 │
└───────┘     └───────┘

After appending:
┌───────┐
│ Row 1 │ (from Table A)
│ Row 2 │ (from Table A)
│ Row 1 │ (from Table B)
│ Row 2 │ (from Table B)
└───────┘

Build-Up - 7 Steps

1

Foundation

Understanding tables and rows

Concept: Learn what tables and rows are in Excel and how data is organized.

In Excel, data is arranged in rows (horizontal lines) and columns (vertical lines). A table is a group of rows and columns with related data. Each row represents one record or item, like a person or a sale.

Result

You can identify rows and columns and understand how data is structured in tables.

Knowing how data is organized helps you see why combining rows from tables makes sense when appending.

2

Foundation

Loading data into Power Query

Concept: Learn how to bring Excel tables into Power Query to prepare for appending.

Power Query is a tool in Excel that helps clean and combine data. You can load tables into Power Query by selecting the table and choosing 'From Table/Range' in the Data tab.

Result

Tables are loaded into Power Query where you can transform and combine them.

Loading data into Power Query is the first step before you can append queries.

3

Intermediate

Appending two queries step-by-step

🤔Before reading on: do you think appending merges columns side-by-side or stacks rows vertically? Commit to your answer.

Concept: Learn how to append two queries in Power Query by stacking their rows.

In Power Query, after loading two tables, go to the Home tab and select 'Append Queries'. Choose the two tables to combine. Power Query stacks the rows from the second table below the first, creating one combined query.

Result

A new query appears with all rows from both tables stacked vertically.

Understanding that appending stacks rows—not merges columns—prevents confusion when combining data.

4

Intermediate

Appending multiple queries at once

🤔Before reading on: can you append more than two tables at once in Power Query? Commit to yes or no.

Concept: Learn how to append more than two queries in one step.

In Power Query's 'Append Queries' dialog, choose 'Three or more tables'. Then select all tables you want to append. Power Query stacks all rows from these tables into one combined query.

Result

One query contains all rows from all selected tables stacked vertically.

Knowing you can append many tables at once saves time and simplifies workflows.

5

Intermediate

Handling different columns when appending

🤔Before reading on: what happens if tables have different columns when appended? Commit to your guess.

Concept: Learn how Power Query manages columns that don't match when appending tables.

If tables have different columns, Power Query creates all columns from all tables. Missing values in some rows show as null (empty). You can later fill or remove these nulls as needed.

Result

Appended query has all columns combined; some cells may be empty if columns didn't exist in original tables.

Understanding how Power Query handles mismatched columns helps you prepare data before appending.

6

Advanced

Appending queries with transformations

🤔Before reading on: do you think you can transform data before or after appending? Commit to your answer.

Concept: Learn how to clean or change data in each query before appending for better results.

You can apply filters, rename columns, or change data types in each query before appending. This ensures the combined data is consistent and ready for analysis.

Result

Appended query contains clean, uniform data from all sources.

Transforming data before appending prevents errors and makes combined data easier to use.

7

Expert

Performance tips for large appended queries

🤔Before reading on: do you think appending many large tables slows down Power Query? Commit to yes or no.

Concept: Learn how appending large datasets affects performance and how to optimize it.

Appending many large tables can slow down refresh times. To improve speed, filter data early, remove unnecessary columns before appending, and disable background data previews. Also, use incremental refresh if available.

Result

Faster query refresh and smoother data handling even with big datasets.

Knowing performance impacts helps you design efficient data workflows in real projects.

Under the Hood

Power Query reads each table's data and creates a list of rows for each. When appending, it combines these lists by placing one list after another, creating a single list of rows. It aligns columns by name, adding nulls where columns don't exist in some tables. This combined list becomes the new query output.

Why designed this way?

Appending was designed to simplify combining similar datasets without complex joins. Stacking rows is a natural way to merge data collected over time or from different sources. Aligning columns by name ensures data integrity even if tables differ slightly.

┌─────────────┐   ┌─────────────┐
│ Table 1    │   │ Table 2    │
│ Row A1    │   │ Row B1    │
│ Row A2    │   │ Row B2    │
└─────┬─────┘   └─────┬─────┘
      │               │
      │               │
      └───────┬───────┘
              │
      ┌───────▼────────┐
      │ Appended Query │
      │ Row A1         │
      │ Row A2         │
      │ Row B1         │
      │ Row B2         │
      └────────────────┘

Myth Busters - 4 Common Misconceptions

Quick: Does appending queries merge columns side-by-side? Commit to yes or no.

Common Belief: Appending queries merges tables side-by-side like a horizontal join.

Reality: Appending stacks tables vertically by adding rows from one below another, not merging columns.

Why it matters: Confusing appending with merging leads to wrong data layouts and analysis errors.

Quick: Can you append tables with different columns without issues? Commit to yes or no.

Common Belief: Tables must have exactly the same columns to append successfully.

Reality: Power Query appends tables with different columns by including all columns and filling missing values with nulls.

Why it matters: Expecting identical columns can stop you from appending useful data that differs slightly.

Quick: Does appending automatically remove duplicate rows? Commit to yes or no.

Common Belief: Appending queries removes duplicate rows automatically.

Reality: Appending simply stacks rows; it does not remove duplicates unless you apply extra steps.

Why it matters: Assuming duplicates are removed can cause incorrect data counts and analysis.

Quick: Is appending always fast regardless of data size? Commit to yes or no.

Common Belief: Appending queries is always quick, no matter how much data you have.

Reality: Appending large datasets can slow down Power Query and Excel performance.

Why it matters: Ignoring performance can cause slow reports and frustrated users.

Expert Zone

1

Appending queries preserves the data types of columns, but mismatched types across tables can cause errors or unexpected type promotion.

2

The order of tables in the append operation matters because rows are stacked in that sequence, affecting data analysis and reporting.

3

Appending queries does not automatically refresh source data; you must refresh queries manually or set up automatic refresh.

When NOT to use

Appending is not suitable when you need to combine data side-by-side based on matching keys; in that case, merging queries is better. Also, if data sets have very different structures, appending may create confusing null-filled columns; consider restructuring data first.

Production Patterns

Professionals use appending to consolidate monthly sales reports from multiple regions into one master report. They often clean and standardize each region's data before appending. In dashboards, appended queries feed combined data models for unified analysis.

Connections

Database UNION operation

Appending queries in Excel Power Query works like the UNION operation in SQL databases, combining rows from multiple tables.

Understanding UNION in databases helps grasp how appending stacks data vertically in spreadsheets.

Data consolidation in accounting

Appending queries is similar to consolidating financial statements from different departments into one report.

Knowing how accountants combine reports helps understand why appending is useful for combining similar data sets.

Stacking blocks in construction

Appending is like stacking building blocks one on top of another to create a taller structure.

Seeing data as blocks stacked vertically clarifies why appending adds rows rather than columns.

Common Pitfalls

#1 Trying to append tables with different column names without preparation.

Wrong approach:

Appending Table1 and Table2 directly when Table2 has columns named differently or extra columns.

Correct approach:

Rename columns in each table to match before appending, or accept nulls for missing columns.

Root cause:

Misunderstanding that Power Query aligns columns by name, not position.

#2 Appending queries and expecting duplicates to be removed automatically.

Wrong approach:

Appending two tables with overlapping data and using the result without removing duplicates.

Correct approach:

After appending, use 'Remove Duplicates' step to clean combined data.

Root cause:

Assuming appending merges unique data rather than stacking all rows.

#3 Appending very large tables without filtering or reducing columns first.

Wrong approach:

Appending full raw data from many sources causing slow refresh and crashes.

Correct approach:

Filter rows and remove unnecessary columns in each query before appending.

Root cause:

Not optimizing data size before combining leads to performance issues.

Key Takeaways

Appending queries stacks tables vertically by adding rows from one table below another to create a combined dataset.

Power Query aligns columns by name when appending, filling missing values with nulls if columns differ.

Appending does not merge columns side-by-side or remove duplicates automatically; those require different steps.

You can append two or many tables at once, but preparing data with consistent columns improves results.

Performance can slow with large appended datasets, so filtering and cleaning data before appending is important.