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SQLで進めるデータドリブンな意思決定

Tim Verdonck

Professor Statistics and Data Science

後続のSELECT文 ― 女優

クエリ1:

SELECT *
FROM actors
WHERE gender = 'female';

| actor_id | name          | year_of_birth | nationality | gender |
|----------|---------------|---------------|-------------|--------|
| 1        | Abbie Cornish | 1982          | Australia   | female |
| 4        | Amy Adams     | 1974          | USA         | female |

後続のSELECT文 ― 女優

SELECT * -- Query 1
FROM actors
WHERE gender = 'female';

クエリ1の結果をnationalityでグループ化。
各国で最年長・最年少の生年を出す。

SELECT af.nationality, 
       MIN(af.year_of_birth), 
       MAX(af.year_of_birth)
FROM
    (SELECT *
    FROM actors
    WHERE gender = 'female') AS af
GROUP BY af.nationality;

後続SELECTの結果 ― 女優

SELECT af.nationality, 
       MIN(af.year_of_birth), 
       MAX(af.year_of_birth)
FROM
    (SELECT *
    FROM actors
    WHERE gender = 'female') AS af
GROUP BY af.nationality;

| nationality | min  | max  |
|-------------|------|------|
| Italy       | 1976 | 1976 |
| Iran        | 1952 | 1952 |
| USA         | 1945 | 1993 |

各顧客はいくら使ったか？

第1歩: moviesのrenting_priceをrentingに結合。

SELECT r.customer_id,
       m.renting_price
FROM renting AS r
LEFT JOIN movies AS m
ON r.movie_id=m.movie_id;

| customer_id | renting_price |
|-------------|---------------|
| 41          | 2.59          |
| 10          | 2.79          |
| 108         | 2.39          |
| 39          | 1.59          |
| 104         | 1.69          |

各顧客はいくら使ったか？

第2歩:
- 第1歩の結果をcustomer_idでグループ化
- renting_priceを合計

SELECT rm.customer_id, 
           SUM(rm.renting_price)
FROM
       (SELECT r.customer_id, 
               m.renting_price
       FROM renting AS r
       LEFT JOIN movies AS m
       ON r.movie_id=m.movie_id) AS rm
GROUP BY rm.customer_id;

各顧客はいくら使ったか？

| customer_id | sum   |
|-------------|-------|
| 116         | 7.47  |
| 87          | 17.53 |
| 71          | 6.87  |
| 68          | 1.59  |
| 51          | 4.87  |

Passons à la pratique !

SQLで進めるデータドリブンな意思決定