# The Matrix: PIVOT Reloaded

DB Quacks SQL Tutorial · level 31 · chapter 6

Agent Smith Duck appears in dark sunglasses. "Welcome to the Matrix! Reality is about to change. Transform boring row data into a cross-tabulation matrix - species as rows, pond names as columns. Bend the data!"

## Task

Create a cross-tabulation showing species as rows and pond names as columns with visit counts by joining the ducks table with 'data/pond_visits.csv'. You will be transforming row data into a matrix format.

## Hint

Look for a statement that can transform rows into columns based on unique values.

## Expected result

A pivot table with species as rows and pond names as columns showing visit counts.

## Tables

### `duck_diaries` (10 rows)

| column | type |
| --- | --- |
| diary_id | BIGINT |
| duck_id | BIGINT |
| entry_date | DATE |
| diary_text | VARCHAR |
| mood | VARCHAR |

### `duck_surveys` (5000 rows)

| column | type |
| --- | --- |
| survey_id | BIGINT |
| duck_id | BIGINT |
| age | BIGINT |
| favorite_food | VARCHAR |
| favorite_pond | BIGINT |
| swimming_rating | BIGINT |
| migration_preference | VARCHAR |
| social_behavior | VARCHAR |
| health_status | VARCHAR |
| activity_level | VARCHAR |
| survey_date | DATE |
| survey_location | BIGINT |

### `ducks` (15 rows)

| column | type |
| --- | --- |
| id | BIGINT |
| name | VARCHAR |
| age | BIGINT |
| species | VARCHAR |
| birth_date | DATE |
| arrival_date | DATE |

### `ponds` (3 rows)

| column | type |
| --- | --- |
| pond_id | BIGINT |
| pond_name | VARCHAR |
| location_lat | DOUBLE |
| location_lng | DOUBLE |
| capacity | BIGINT |
| features | VARCHAR[] |
| amenities | VARCHAR[] |

## Files

### `data/pond_visits.csv` (40 rows)

Download: https://dbquacks.com/data/pond_visits.csv

| column | type |
| --- | --- |
| visit_id | BIGINT |
| duck_id | BIGINT |
| pond_id | BIGINT |
| visit_date | DATE |
| duration_minutes | BIGINT |

## Data

The tables live in a DuckDB database: https://dbquacks.com/data/databases/tutorial.duckdb

To query it outside the browser, attach it read-only:

```sql
ATTACH 'https://dbquacks.com/data/databases/tutorial.duckdb' AS db (READ_ONLY);
USE db;
```

Play it in the browser: https://dbquacks.com/tutorial/31

## Reference

https://duckdb.org/docs/stable/sql/statements/pivot.html