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# Lab | SQL basics (selection and aggregation)

## Introduction

In this lab, you will be using the `files_for_lab/lab1_bank.sqlite` database. Load it into DB browser for sqlite, and there you will find a `bank` database which we will use for the following exercise.

Open the `lab1_bank.sqlite` database in DB Browser for SQLite by selecting **Open Database** and choosing the `lab1_bank.sqlite` file. Once it's open, you can start working on your lab in the **Execute SQL** section. Don't forget to save your code regularly.


Here, we will practice selecting and projecting data. You can finish all questions with only those clauses:

- `SELECT`
- `SELECT DISTINCT`
- `FROM`
- `WHERE`
- `ORDER BY`
- `LIMIT`

You can save your solutions in a file `solutions.sql`.

## Instructions

Assume that any `_id` columns are incremental, meaning that higher ids always occur after lower ids. For example, a client with a higher `client_id` joined the bank after a client with a lower `client_id`.

### Query 1

Get the `id` values of the first 5 clients from `district_id` with a value equals to 1.

Expected result:

```shell
2
3
22
23
28
```

### Query 2

In the `client` table, get an `id` value of the last client where the `district_id` equals to 72.

Expected result:

```shell
13576
```

### Query 3

Get the 3 lowest amounts in the `loan` table.

Expected result:

```shell
4980
5148
7656
```

### Query 4

What are the possible values for `status`, ordered alphabetically in ascending order in the `loan` table?

Expected result:

```shell
A
B
C
D
```

### Query 5

What is the `loan_id` of the highest payment received in the `loan` table?

Expected result:

```shell
6415
```

### Query 6

What is the loan `amount` of the lowest 5 `account_id`s in the `loan` table? Show the `account_id` and the corresponding `amount`

Expected result:

```shell
#id amount
2 80952
19 30276
25 30276
37 318480
38 110736
```

### Query 7

What are the `account_id`s with the lowest loan `amount` that have a loan `duration` of 60 in the `loan` table?

Expected result:

```shell
10954
938
10711
1766
10799
```

### Query 8

What are the unique values of `k_symbol` in the `order` table?

Note: There shouldn't be a table name `order`, since `order` is reserved from the `ORDER BY` clause. You have to use backticks to escape the `order` table name.

Expected result:

```shell
LEASING
POJISTNE
SIPO
UVER
```

### Query 9

In the `order` table, what are the `order_id`s of the client with the `account_id` 34?

Expected result:

```shell
29445
29446
29447
```

### Query 10

In the `order` table, which `account_id`s were responsible for orders between `order_id` 29540 and `order_id` 29560 (inclusive)?

Expected result:

```shell
88
90
96
97
```

### Query 11

In the `order` table, what are the individual amounts that were sent to (`account_to`) id 30067122?

Expected result:

```shell
5123
```

### Query 12

In the `trans` table, show the `trans_id`, `date`, `type` and `amount` of the 10 first transactions from `account_id` 793 in chronological order, from newest to oldest.

Expected result:

```shell
3556468 981231 PRIJEM 78.6
233254 981216 VYDAJ 600
233104 981212 VYDAJ 1212
233248 981211 VYDAJ 851
233176 981207 VYDAJ 204
3556467 981130 PRIJEM 75.1
233395 981130 VYDAJ 14.6
233103 981112 VYDAJ 1212
233247 981111 VYDAJ 851
233175 981107 VYDAJ 204
```

### Query 13

In the `client` table, of all districts with a `district_id` lower than 10, how many clients are from each `district_id`? Show the results sorted by the `district_id` in ascending order.

Expected result:

```shell
1 663
2 46
3 63
4 50
5 71
6 53
7 45
8 69
9 60
```

### Query 14

In the `card` table, how many cards exist for each `type`? Rank the result starting with the most frequent `type`.

Expected result:

```shell
classic 659
junior 145
gold 88
```

### Query 15

Using the `loan` table, print the top 10 `account_id`s based on the sum of all of their loan amounts.

Expected result:

```shell
7542 590820
8926 566640
2335 541200
817 538500
2936 504000
7049 495180
10451 482940
6950 475680
7966 473280
339 468060
```

### Query 16

In the `loan` table, retrieve the number of loans issued for each day, before (excl) 930907, ordered by date in descending order.

Expected result:

```
930906 1
930803 1
930728 1
930711 1
930705 1
```

### Query 17

In the `loan` table, for each day in December 1997, count the number of loans issued for each unique loan duration, ordered by date and duration, both in ascending order. You can ignore days without any loans in your output.

Expected result:

```shell
971206 24 1
971206 36 1
971208 12 3
971209 12 1
971209 24 1
971210 12 1
971211 24 1
971211 48 1
971213 24 1
971220 36 1
971221 36 1
971224 60 1
971225 24 1
971225 60 1
971226 60 1
971227 48 1
971228 12 1
971228 36 1
971228 48 2
971231 60 1
```

### Query 18

In the `trans` table, for `account_id` 396, sum the amount of transactions for each type (`VYDAJ` = Outgoing, `PRIJEM` = Incoming). Your output should have the `account_id`, the `type` and the sum of amount, named as `total_amount`. Sort alphabetically by type.

Expected result:

```shell
396 PRIJEM 1028138.6999740601
396 VYDAJ 1485814.400024414
```
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