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| 1 | +# Grouping Data in SQL |
| 2 | + |
| 3 | +When you work with a lot of data, you often want to **combine rows that have the same values** in certain columns and calculate something for each group. |
| 4 | +In SQL, this is done with the **`GROUP BY`** clause. |
| 5 | + |
| 6 | + |
| 7 | + |
| 8 | +## Why Use GROUP BY? |
| 9 | + |
| 10 | +Imagine you have a `sales` table: |
| 11 | + |
| 12 | +| id | product | category | quantity | price | |
| 13 | +|----|-----------|-----------|----------|-------| |
| 14 | +| 1 | Apple | Fruit | 10 | 2.5 | |
| 15 | +| 2 | Orange | Fruit | 5 | 3.0 | |
| 16 | +| 3 | Carrot | Vegetable | 7 | 1.5 | |
| 17 | +| 4 | Apple | Fruit | 8 | 2.5 | |
| 18 | + |
| 19 | +If you want **total quantity sold for each category**, you can group the rows by `category`. |
| 20 | + |
| 21 | + |
| 22 | + |
| 23 | +## GROUP BY Syntax |
| 24 | + |
| 25 | +```sql |
| 26 | +SELECT column1, column2, ..., aggregate_function(column) |
| 27 | +FROM table_name |
| 28 | +GROUP BY column1, column2, ...; |
| 29 | +```` |
| 30 | + |
| 31 | +* **`aggregate_function`**: Functions that calculate a value for a group, such as: |
| 32 | + |
| 33 | + * `COUNT()` → Counts rows |
| 34 | + * `SUM()` → Adds values |
| 35 | + * `AVG()` → Calculates average |
| 36 | + * `MIN()` → Finds smallest value |
| 37 | + * `MAX()` → Finds largest value |
| 38 | + |
| 39 | + |
| 40 | +## Example: GROUP BY with SUM |
| 41 | + |
| 42 | +```sql |
| 43 | +SELECT category, SUM(quantity) AS total_quantity |
| 44 | +FROM sales |
| 45 | +GROUP BY category; |
| 46 | +``` |
| 47 | + |
| 48 | +**Result:** |
| 49 | + |
| 50 | +| category | total\_quantity | |
| 51 | +| --------- | --------------- | |
| 52 | +| Fruit | 23 | |
| 53 | +| Vegetable | 7 | |
| 54 | + |
| 55 | +**How it works:** |
| 56 | + |
| 57 | +1. SQL looks at the `category` column. |
| 58 | +2. Rows with the same category are grouped together. |
| 59 | +3. The `SUM(quantity)` is calculated for each group. |
| 60 | + |
| 61 | + |
| 62 | + |
| 63 | +## GROUP BY with Multiple Columns |
| 64 | + |
| 65 | +You can group by **more than one column**. |
| 66 | + |
| 67 | +```sql |
| 68 | +SELECT category, product, SUM(quantity) AS total_quantity |
| 69 | +FROM sales |
| 70 | +GROUP BY category, product; |
| 71 | +``` |
| 72 | + |
| 73 | +Now each unique **(category, product)** pair is its own group. |
| 74 | + |
| 75 | + |
| 76 | + |
| 77 | +## Filtering Groups with HAVING |
| 78 | + |
| 79 | +`WHERE` filters **rows before grouping**. |
| 80 | +`HAVING` filters **groups after grouping**. |
| 81 | + |
| 82 | +Example: Show only categories where total quantity > 10. |
| 83 | + |
| 84 | +```sql |
| 85 | +SELECT category, SUM(quantity) AS total_quantity |
| 86 | +FROM sales |
| 87 | +GROUP BY category |
| 88 | +HAVING SUM(quantity) > 10; |
| 89 | +``` |
| 90 | + |
| 91 | +**Result:** |
| 92 | + |
| 93 | +| category | total\_quantity | |
| 94 | +| -------- | --------------- | |
| 95 | +| Fruit | 23 | |
| 96 | + |
| 97 | + |
| 98 | + |
| 99 | +## Difference Between WHERE and HAVING |
| 100 | + |
| 101 | +| Clause | Filters On | Works With Aggregates? | |
| 102 | +| ------ | --------------- | ---------------------- | |
| 103 | +| WHERE | Individual rows | ❌ (no aggregates) | |
| 104 | +| HAVING | Grouped results | ✅ (with aggregates) | |
| 105 | + |
| 106 | + |
| 107 | + |
| 108 | +## Common Aggregate Functions |
| 109 | + |
| 110 | +| Function | Description | Example | |
| 111 | +| ----------- | ----------------- | --------------- | |
| 112 | +| COUNT(\*) | Counts all rows | `COUNT(*)` | |
| 113 | +| SUM(column) | Adds all values | `SUM(quantity)` | |
| 114 | +| AVG(column) | Average of values | `AVG(price)` | |
| 115 | +| MIN(column) | Minimum value | `MIN(price)` | |
| 116 | +| MAX(column) | Maximum value | `MAX(price)` | |
| 117 | + |
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