# JSON and the Amazing Technicolor Dreamcoat

DB Quacks SQL Tutorial · level 15 · chapter 3

Tech-savvy beaver swims up with a tablet. "Greetings! Our pond location data is stored in modern JSON format instead of CSV. JSON handles complex, nested information beautifully! Can you read this JSON file directly?"

## Task

Read and display specific fields from the external JSON file 'data/pond_locations.json'. Show the pond_id, pond_name, capacity, water_type, and depth_meters fields. You will be working with a JSON file containing pond location data.

## Hint

Similar to CSV reading, but look for a function specifically designed for JSON format.

## Expected result

A table showing pond_id, pond_name, capacity, water_type, and depth_meters from the pond_locations.json file.

## 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_locations.json` (3 rows)

Download: https://dbquacks.com/data/pond_locations.json

| column | type |
| --- | --- |
| pond_id | BIGINT |
| pond_name | VARCHAR |
| location | STRUCT(latitude DOUBLE, longitude DOUBLE, features VARCHAR[]) |
| capacity | BIGINT |
| amenities | VARCHAR[] |
| water_type | VARCHAR |
| depth_meters | DOUBLE |
| is_public | BOOLEAN |
| maintenance_schedule | VARCHAR |

## 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/15

## Reference

https://duckdb.org/docs/stable/guides/file_formats/json_import.html