Task: equi-join-detect (source dataset: Auto-BI)

Your are given a database with related tables used for business intelligence analysis. Your task is to identify all key/foreign-key join relationships between the tables for this database. Recall that a join is a relationship between two tables, that allows rows from one table to be combined with rows from another, based on a set of common join columns.
 
 
No explanation needed. Please return all join relationships in the following JSON format:
{
  "joins": [
    {
      "from_table": "table-1",
      "from_column": "column-1",
      "to_table": "table-2",
      "to_column": "column-3"
    }, 
	...
  ]
}

Tables:

Table: average_cases_per_date
|    average_cases_per_date | Date_reported           |
|--------------------------:|:------------------------|
|                0          | 2020-01-03 00:00:00.000 |
|                0.00425532 | 2020-01-04 00:00:00.000 |
|                0          | 2020-01-05 00:00:00.000 |
|                0.012766   | 2020-01-06 00:00:00.000 |
|                0          | 2020-01-07 00:00:00.000 |
|                0          | 2020-01-08 00:00:00.000 |
|                0          | 2020-01-09 00:00:00.000 |
|                0          | 2020-01-10 00:00:00.000 |
|                0.174468   | 2020-01-11 00:00:00.000 |
|                0          | 2020-01-12 00:00:00.000 |


Table: average_death_per_date
| Date_reported           |   average_death_per_date |
|:------------------------|-------------------------:|
| 2020-01-03 00:00:00.000 |               0          |
| 2020-01-04 00:00:00.000 |               0          |
| 2020-01-05 00:00:00.000 |               0          |
| 2020-01-06 00:00:00.000 |               0          |
| 2020-01-07 00:00:00.000 |               0          |
| 2020-01-08 00:00:00.000 |               0          |
| 2020-01-09 00:00:00.000 |               0          |
| 2020-01-10 00:00:00.000 |               0          |
| 2020-01-11 00:00:00.000 |               0.00425532 |
| 2020-01-12 00:00:00.000 |               0          |


Table: average_death_per_region
| WHO_region   |   average_death_per_region |
|:-------------|---------------------------:|
| EMRO         |                 10.2283    |
| EURO         |                 14.0465    |
| AFRO         |                  1.89104   |
| WPRO         |                  1.39683   |
| AMRO         |                 37.7097    |
| SEARO        |                 37.6761    |
| Other        |                  0.0481481 |


Table: average_per_region
| WHO_region   |   average_region_cases |
|:-------------|-----------------------:|
| EMRO         |              396.92    |
| EURO         |              342.004   |
| AFRO         |               87.0972  |
| WPRO         |               63.9763  |
| AMRO         |             1122.09    |
| SEARO        |             2293.1     |
| Other        |                2.74444 |


Table: migration_population (2)
| country                |   year |   population |   pop_density | net_migration   | migration_perc   | iso3c   | iso2c   | region                     | adminregion   | incomeLevel   | lendingType    | capitalCity      | longitude   | latitude   |
|:-----------------------|-------:|-------------:|--------------:|:----------------|:-----------------|:--------|:--------|:---------------------------|:--------------|:--------------|:---------------|:-----------------|:------------|:-----------|
| Andorra                |   2018 |        77006 |     163.843   |                 |                  | AND     | AD      | Europe & Central Asia      |               | High income   | Not classified | Andorra la Vella | 1/1/5218    | 42.5075    |
| Aruba                  |   2018 |       105845 |     588.028   |                 |                  | ABW     | AW      | Latin America & Caribbean  |               | High income   | Not classified | Oranjestad       | -70.0167    | 12/1/5167  |
| Australia              |   2018 |     24992369 |       3.24913 |                 |                  | AUS     | AU      | East Asia & Pacific        |               | High income   | Not classified | Canberra         | 149.129     | -35.282    |
| Austria                |   2018 |      8847037 |     107.207   |                 |                  | AUT     | AT      | Europe & Central Asia      |               | High income   | Not classified | Vienna           | 16.3798     | 48.2201    |
| Bahamas, The           |   2018 |       385640 |      38.5255  |                 |                  | BHS     | BS      | Latin America & Caribbean  |               | High income   | Not classified | Nassau           | -77.339     | 25.0661    |
| Bahrain                |   2018 |      1569439 |    2017.27    |                 |                  | BHR     | BH      | Middle East & North Africa |               | High income   | Not classified | Manama           | 50.5354     | 26.1921    |
| Barbados               |   2018 |       286641 |     666.607   |                 |                  | BRB     | BB      | Latin America & Caribbean  |               | High income   | Not classified | Bridgetown       | -59.6105    | 13.0935    |
| Belgium                |   2018 |     11422068 |     377.215   |                 |                  | BEL     | BE      | Europe & Central Asia      |               | High income   | Not classified | Brussels         | 4.36761     | 50.8371    |
| Bermuda                |   2018 |        63968 |    1184.59    |                 |                  | BMU     | BM      | North America              |               | High income   | Not classified | Hamilton         | -64.706     | 32.3293    |
| British Virgin Islands |   2018 |        29802 |     198.68    |                 |                  | VGB     | VG      | Latin America & Caribbean  |               | High income   | Not classified | Road Town        | -64.623056  | 18.431389  |


Table: migration_population (3)
| country                |   year |   population |   pop_density | net_migration   | migration_perc   | iso3c   | iso2c   | region                     | adminregion   | incomeLevel   | lendingType    | capitalCity      | longitude   | latitude   |
|:-----------------------|-------:|-------------:|--------------:|:----------------|:-----------------|:--------|:--------|:---------------------------|:--------------|:--------------|:---------------|:-----------------|:------------|:-----------|
| Andorra                |   2018 |        77006 |     163.843   |                 |                  | AND     | AD      | Europe & Central Asia      |               | High income   | Not classified | Andorra la Vella | 1/1/5218    | 42.5075    |
| Aruba                  |   2018 |       105845 |     588.028   |                 |                  | ABW     | AW      | Latin America & Caribbean  |               | High income   | Not classified | Oranjestad       | -70.0167    | 12/1/5167  |
| Australia              |   2018 |     24992369 |       3.24913 |                 |                  | AUS     | AU      | East Asia & Pacific        |               | High income   | Not classified | Canberra         | 149.129     | -35.282    |
| Austria                |   2018 |      8847037 |     107.207   |                 |                  | AUT     | AT      | Europe & Central Asia      |               | High income   | Not classified | Vienna           | 16.3798     | 48.2201    |
| Bahamas, The           |   2018 |       385640 |      38.5255  |                 |                  | BHS     | BS      | Latin America & Caribbean  |               | High income   | Not classified | Nassau           | -77.339     | 25.0661    |
| Bahrain                |   2018 |      1569439 |    2017.27    |                 |                  | BHR     | BH      | Middle East & North Africa |               | High income   | Not classified | Manama           | 50.5354     | 26.1921    |
| Barbados               |   2018 |       286641 |     666.607   |                 |                  | BRB     | BB      | Latin America & Caribbean  |               | High income   | Not classified | Bridgetown       | -59.6105    | 13.0935    |
| Belgium                |   2018 |     11422068 |     377.215   |                 |                  | BEL     | BE      | Europe & Central Asia      |               | High income   | Not classified | Brussels         | 4.36761     | 50.8371    |
| Bermuda                |   2018 |        63968 |    1184.59    |                 |                  | BMU     | BM      | North America              |               | High income   | Not classified | Hamilton         | -64.706     | 32.3293    |
| British Virgin Islands |   2018 |        29802 |     198.68    |                 |                  | VGB     | VG      | Latin America & Caribbean  |               | High income   | Not classified | Road Town        | -64.623056  | 18.431389  |


Table: migration_population
| country                                       |   year |   population | pop_density   | net_migration   | migration_perc   | iso3c   | iso2c   | region     | adminregion   | incomeLevel   | lendingType   | capitalCity   | longitude   | latitude   |
|:----------------------------------------------|-------:|-------------:|:--------------|:----------------|:-----------------|:--------|:--------|:-----------|:--------------|:--------------|:--------------|:--------------|:------------|:-----------|
| Arab World                                    |   1960 |     92197753 |               |                 |                  | ARB     | 1A      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| Caribbean small states                        |   1960 |      4194710 |               |                 |                  | CSS     | S3      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| Central Europe and the Baltics                |   1960 |     91401764 |               |                 |                  | CEB     | B8      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| Early-demographic dividend                    |   1960 |    980085256 |               |                 |                  | EAR     | V2      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| East Asia & Pacific                           |   1960 |   1040958103 |               |                 |                  | EAS     | Z4      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| East Asia & Pacific (excluding high income)   |   1960 |    894880101 |               |                 |                  | EAP     | 4E      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| East Asia & Pacific (IDA & IBRD countries)    |   1960 |    883445573 |               |                 |                  | TEA     | T4      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| Euro area                                     |   1960 |    265203934 |               |                 |                  | EMU     | XC      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| Europe & Central Asia                         |   1960 |    667253650 |               |                 |                  | ECS     | Z7      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |
| Europe & Central Asia (excluding high income) |   1960 |    275147578 |               |                 |                  | ECA     | 7E      | Aggregates |               | Aggregates    | Aggregates    |               |             |            |


Table: WHO-COVID-19-global-data
| Date_reported           | Country_code   | Country                | WHO_region   |   New_cases |   Cumulative_cases |   New_deaths |   Cumulative_deaths |   Date_reported - Copy.1 |   Date_reported - Copy.2 |   Date_reported - Copy.3 |
|:------------------------|:---------------|:-----------------------|:-------------|------------:|-------------------:|-------------:|--------------------:|-------------------------:|-------------------------:|-------------------------:|
| 2020-01-03 00:00:00.000 | AL             | Albania                | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | AD             | Andorra                | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | AM             | Armenia                | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | AT             | Austria                | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | AZ             | Azerbaijan             | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | BY             | Belarus                | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | BE             | Belgium                | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | BA             | Bosnia and Herzegovina | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | BG             | Bulgaria               | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |
| 2020-01-03 00:00:00.000 | HR             | Croatia                | EURO         |           0 |                  0 |            0 |                   0 |                        1 |                        3 |                     2020 |

 


tables: name: average_cases_per_date
data: average_cases_per_date.csv
name: average_death_per_date
data: average_death_per_date.csv
name: average_death_per_region
data: average_death_per_region.csv
name: average_per_region
data: average_per_region.csv
name: migration_population (2)
data: migration_population (2).csv
name: migration_population (3)
data: migration_population (3).csv
name: migration_population
data: migration_population.csv
name: WHO-COVID-19-global-data
data: WHO-COVID-19-global-data.csv
label: migration_population
country
WHO-COVID-19-global-data
Country
WHO-COVID-19-global-data
Country
migration_population (2)
country
WHO-COVID-19-global-data
Country
migration_population (3)
country
output: {
    "joins": [
        {
            "from_table": "migration_population",
            "from_column": "country",
            "to_table": "WHO-COVID-19-global-data",
            "to_column": "Country"
        },
        {
            "from_table": "WHO-COVID-19-global-data",
            "from_column": "Country",
            "to_table": "migration_population (2)",
            "to_column": "country"
        },
        {
            "from_table": "WHO-COVID-19-global-data",
            "from_column": "Country",
            "to_table": "migration_population (3)",
            "to_column": "country"
        }
    ]
}