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: (i)_WorldmetersAPI
| country             |   cases |   todayCases |   deaths |   todayDeaths |   recovered |   active |   critical |   casesPerOneMillion | updated     | iso2   |   todayRecovered |   deathsPerOneMillion |   tests |   testsPerOneMillion |   population | continent     |   oneCasePerPeople |   oneDeathPerPeople |   oneTestPerPeople | activePerOneMillion   | recoveredPerOneMillion   | criticalPerOneMillion   |
|:--------------------|--------:|-------------:|---------:|--------------:|------------:|---------:|-----------:|---------------------:|:------------|:-------|-----------------:|----------------------:|--------:|---------------------:|-------------:|:--------------|-------------------:|--------------------:|-------------------:|:----------------------|:-------------------------|:------------------------|
| Andorra             |    1966 |            0 |       53 |             0 |        1265 |      648 |          9 |                25435 | 1,60141E+12 | AD     |                0 |                   686 |  137457 |              1778320 |        77296 | Europe        |                 39 |                1458 |                  1 | 8383,36               | 16365,66                 | 116,44                  |
| Anguilla            |       3 |            0 |        0 |             0 |           3 |        0 |          0 |                  200 | 1,60141E+12 | AI     |                0 |                     0 |    1020 |                67837 |        15036 | North America |               5012 |                   0 |                 15 | 0                     | 199,52                   | 0                       |
| Antigua and Barbuda |     101 |            0 |        3 |             0 |          92 |        6 |          0 |                 1029 | 1,60141E+12 | AG     |                0 |                    31 |    2701 |                27526 |        98127 | North America |                972 |               32709 |                 36 | 61,15                 | 937,56                   | 0                       |
| Argentina           |  723132 |            0 |    16113 |             0 |      576715 |   130304 |       3678 |                15964 | 1,60141E+12 | AR     |                0 |                   356 | 1926717 |                42535 |     45296882 | South America |                 63 |                2811 |                 24 | 2876,67               | 12731,89                 | 81,2                    |
| Barbados            |     190 |            0 |        7 |             0 |         178 |        5 |          0 |                  661 | 1,60141E+12 | BB     |                0 |                    24 |   23032 |                80122 |       287462 | North America |               1513 |               41066 |                 12 | 17,39                 | 619,21                   | 0                       |
| Benin               |    2340 |            0 |       40 |             0 |        1960 |      340 |          0 |                  192 | 1,60141E+12 | BJ     |                0 |                     3 |  194235 |                15923 |     12198114 | Africa        |               5213 |              304953 |                 63 | 27,87                 | 160,68                   | 0                       |
| Bermuda             |     181 |            0 |        9 |             0 |         167 |        5 |          0 |                 2909 | 1,60141E+12 | BM     |                0 |                   145 |   63640 |              1022806 |        62221 | North America |                344 |                6913 |                  1 | 80,36                 | 2683,98                  | 0                       |
| Botswana            |    3172 |            0 |       16 |             0 |         710 |     2446 |          1 |                 1342 | 1,60141E+12 | BW     |                0 |                     7 |  184076 |                77900 |      2362964 | Africa        |                745 |              147685 |                 13 | 1035,14               | 300,47                   | 0,42                    |
| Brunei              |     146 |            0 |        3 |             0 |         142 |        1 |          0 |                  333 | 1,60141E+12 | BN     |                0 |                     7 |   58487 |               133380 |       438500 | Asia          |               3003 |              146167 |                  7 | 2,28                  | 323,83                   | 0                       |
| Bulgaria            |   20271 |            0 |      807 |             0 |       14339 |     5125 |         42 |                 2923 | 1,60141E+12 | BG     |                0 |                   116 |  519613 |                74923 |      6935323 | Europe        |                342 |                8594 |                 13 | 738,97                | 2067,53                  | 6,06                    |


Table: (_i)_CountryNamesTranslation
| 2char country code   | Forms of country names                                    | Country Name (usual)   | Possible mismatch   |
|:---------------------|:----------------------------------------------------------|:-----------------------|:--------------------|
| XY                   | # Undefined                                               | # Undefined            |                     |
| AF                   | Afghanistan                                               | Afghanistan            |                     |
| GB                   | Akrotiri and Dhekelia                                     | United Kingdom         |                     |
| AX                   | ?land                                                     | Aland Islands          |                     |
| AX                   | Aland Islands                                             | Aland Islands          |                     |
| AX                   | ?land Islands                                             | Aland Islands          |                     |
| AL                   | Albania                                                   | Albania                |                     |
| DZ                   | Algeria                                                   | Algeria                |                     |
| AQ                   | All land and ice shelves south of the 60th parallel south | Antarctica             |                     |
| AS                   | American Samoa                                            | American Samoa         |                     |


Table: @Info
| About this report                                                                                                                                                                       | Data Hint                                                                       | Authors                        | Weblink                          |
|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------|:-------------------------------|:---------------------------------|
| This report is regulary updated and show official Corona Covid-19 Data from official sources. This report is free to share and is available as webreport on CoronaDataSource.org portal | All data used in this report are published as open data at CoronaDataSource.org | Report made by CDS Specialists | https:\\www.coronadatasource.org |


Table: @Last_Update
|   Number of rows | Last Power BI Refresh   | Date_Last_Update        |
|-----------------:|:------------------------|:------------------------|
|              267 | 29.9.2020 22:23:56      | 2020-09-28 00:00:00.000 |


Table: CDS_Infected_Deaths_Cured
| Province/State   | Country/Region   | Date                    |   Infected |   Deaths |   Cured | Error Check   | China / Others   | Error check Countries   | 2char_Country_Code   |   Sick |
|:-----------------|:-----------------|:------------------------|-----------:|---------:|--------:|:--------------|:-----------------|:------------------------|:---------------------|-------:|
|                  | Afghanistan      | 2020-02-24 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-02-25 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-02-26 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-02-27 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-02-28 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-02-29 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-03-01 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-03-02 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-03-03 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |
|                  | Afghanistan      | 2020-03-04 00:00:00.000 |          1 |        0 |       0 | OK            | Other countries  | OK                      | AF                   |      1 |


Table: CDS_Last numbers
| Country/Region      |   Infected |   Deaths |   Cured | 2char_Country_Code   | Number of Cases   |   Sick |   % of infected |   % of sick |   % Death Rate | Severity   |   Population num |   Index Infected |   Index Severity | updated     |   todayCases |   todayDeaths |   todayRecovered |   Serious, Critical |   casesPerOneMillion |   deathsPerOneMillion |   tests |   testsPerOneMillion |   population | continent     |   oneCasePerPeople |   oneDeathPerPeople |   oneTestPerPeople |   activePerOneMillion |   recoveredPerOneMillion |   criticalPerOneMillion | Date                    |
|:--------------------|-----------:|---------:|--------:|:---------------------|:------------------|-------:|----------------:|------------:|---------------:|:-----------|-----------------:|-----------------:|-----------------:|:------------|-------------:|--------------:|-----------------:|--------------------:|---------------------:|----------------------:|--------:|---------------------:|-------------:|:--------------|-------------------:|--------------------:|-------------------:|----------------------:|-------------------------:|------------------------:|:------------------------|
| Anguilla            |          3 |        0 |       3 | AI                   | "1+"              |      0 |     0.00019996  | 0           |     0          | <0,05%     |            15003 |                1 |                1 | 1,60141E+12 |            0 |             0 |                0 |                   0 |                  200 |                     0 |    1020 |                67837 |        15036 | North America |               5012 |                   0 |                 15 |                     0 |                      200 |                       0 | 2020-09-29 00:00:00.000 |
| Antigua and Barbuda |        101 |        3 |      92 | AG                   | "100+"            |      6 |     0.00103136  | 6.12689e-05 |     0.029703   | <0,05%     |            97929 |                3 |                3 | 1,60141E+12 |            0 |             0 |                0 |                   0 |                 1029 |                    31 |    2701 |                27526 |        98127 | North America |                972 |               32709 |                 36 |                    61 |                      938 |                       0 | 2020-09-29 00:00:00.000 |
| Barbados            |        190 |        7 |     178 | BB                   | "100+"            |      5 |     0.000661157 | 1.73989e-05 |     0.0368421  | <0,05%     |           287375 |                3 |                2 | 1,60141E+12 |            0 |             0 |                0 |                   0 |                  661 |                    24 |   23032 |                80122 |       287462 | North America |               1513 |               41066 |                 12 |                    17 |                      619 |                       0 | 2020-09-29 00:00:00.000 |
| Benin               |       2340 |       40 |    1960 | BJ                   | "1000+"           |    340 |     0.000193018 | 2.80454e-05 |     0.017094   | <0,05%     |         12123200 |                4 |                2 | 1,60141E+12 |            0 |             0 |                0 |                   0 |                  192 |                     3 |  194235 |                15923 |     12198114 | Africa        |               5213 |              304953 |                 63 |                    28 |                      161 |                       0 | 2020-09-29 00:00:00.000 |
| Bermuda             |        181 |        9 |     167 | BM                   | "100+"            |      5 |     0.00290632  | 8.02852e-05 |     0.0497238  | <0,05%     |            62278 |                3 |                3 | 1,60141E+12 |            0 |             0 |                0 |                   0 |                 2909 |                   145 |   63640 |              1022806 |        62221 | North America |                344 |                6913 |                  1 |                    80 |                     2684 |                       0 | 2020-09-29 00:00:00.000 |
| Bhutan              |        280 |        0 |     210 | BT                   | "100+"            |     70 |     0.000362879 | 9.07196e-05 |     0          | <0,05%     |           771608 |                3 |                3 | 1,60141E+12 |            7 |             0 |                0 |                   0 |                  362 |                     0 |  135061 |               174571 |       773672 | Asia          |               2763 |                   0 |                  6 |                    90 |                      271 |                       0 | 2020-09-29 00:00:00.000 |
| Brunei              |        146 |        3 |     142 | BN                   | "100+"            |      1 |     0.00033373  | 2.28582e-06 |     0.0205479  | <0,05%     |           437479 |                3 |                1 | 1,60141E+12 |            0 |             0 |                0 |                   0 |                  333 |                     7 |   58487 |               133380 |       438500 | Asia          |               3003 |              146167 |                  7 |                     2 |                      324 |                       0 | 2020-09-29 00:00:00.000 |
| Burkina Faso        |       2028 |       57 |    1279 | BF                   | "1000+"           |    692 |     9.70183e-05 | 3.31049e-05 |     0.0281065  | <0,05%     |         20903273 |                4 |                2 | 1,60141E+12 |            0 |             0 |                0 |                   0 |                   96 |                     3 |       0 |                    0 |     21038162 | Africa        |              10374 |              369091 |                  0 |                    33 |                       61 |                       0 | 2020-09-29 00:00:00.000 |
| Burundi             |        502 |        1 |     472 | BI                   | "100+"            |     29 |     4.22176e-05 | 2.43886e-06 |     0.00199203 | <0,05%     |         11890784 |                3 |                1 | 1,60141E+12 |            0 |             0 |                0 |                   0 |                   42 |                     0 |   37522 |                 3134 |     11973721 | Africa        |              23852 |            11973721 |                319 |                     2 |                       39 |                       0 | 2020-09-29 00:00:00.000 |
| Cabo Verde          |       5900 |       59 |    5228 | CV                   | "1000+"           |    613 |     0.0106118   | 0.00110254  |     0.01       | >0,1%      |           555987 |                4 |                5 | 1,60141E+12 |           83 |             0 |               94 |                   0 |                10584 |                   106 |   76576 |               137367 |       557455 | Africa        |                 94 |                9448 |                  7 |                  1100 |                     9378 |                       0 | 2020-09-29 00:00:00.000 |


Table: CountryPopulation
|   Internal_Row_ID | Country       | Country Code   |   Population | Country population size   |   Yearly Change |   Net Change |   Density (P/Km2) |   Land Area (Km2) |   Migrants (net) |   Fertility Rate |   Medium Age |   Urban Pop % |   World Share |
|------------------:|:--------------|:---------------|-------------:|:--------------------------|----------------:|-------------:|------------------:|------------------:|-----------------:|-----------------:|-------------:|--------------:|--------------:|
|                 1 | China         | CN             |   1439323776 | (4) Very large            |          0.0039 |      5540090 |               153 |           9388211 |             -348 |              1.7 |           38 |          0.61 |        0.1847 |
|                 2 | India         | IN             |   1380004385 | (4) Very large            |          0.0099 |     13586631 |               464 |           2973190 |             -533 |              2.2 |           28 |          0.35 |        0.177  |
|                 3 | United States | US             |    331002651 | (4) Very large            |          0.0059 |      1937734 |                36 |           9147420 |              955 |              1.8 |           38 |          0.83 |        0.0425 |
|                 4 | Indonesia     | ID             |    273523615 | (4) Very large            |          0.0107 |      2898047 |               151 |           1811570 |              -99 |              2.3 |           30 |          0.56 |        0.0351 |
|                 5 | Pakistan      | PK             |    220892340 | (4) Very large            |          0.02   |      4327022 |               287 |             77088 |             -233 |              3.6 |           23 |          0.35 |        0.0283 |
|                 6 | Brazil        | BR             |    212559417 | (4) Very large            |          0.0072 |      1509890 |                25 |           8358140 |              212 |              1.7 |           33 |          0.88 |        0.0273 |
|                 7 | Nigeria       | NG             |    206139589 | (4) Very large            |          0.0258 |      5175990 |               226 |             91077 |              -60 |              5.4 |           18 |          0.52 |        0.0264 |
|                 8 | Bangladesh    | BD             |    164689383 | (4) Very large            |          0.0101 |      1643222 |              1265 |             13017 |             -370 |              2.1 |           28 |          0.39 |        0.0211 |
|                 9 | Russia        | RU             |    145934462 | (4) Very large            |          0.0004 |        62206 |                 9 |          16376870 |              182 |              1.8 |           40 |          0.74 |        0.0187 |
|                10 | Mexico        | MX             |    128932753 | (4) Very large            |          0.0106 |      1357224 |                66 |           1943950 |              -60 |              2.1 |           29 |          0.84 |        0.0165 |


Table: Cruise Ship
| Date                    |   Cured |   Deaths |   Sick |   Uninfected / No symptoms |   Daily increase |   Increase last 3days |   Increase last 7days |   % of infected |   % increase daily |   % increase 3days |   % increase 7days | Note                      |   Day |   Prediction 24% daily |   Prediction 33% daily |   Infected / Total Cases |
|:------------------------|--------:|---------:|-------:|---------------------------:|-----------------:|----------------------:|----------------------:|----------------:|-------------------:|-------------------:|-------------------:|:--------------------------|------:|-----------------------:|-----------------------:|-------------------------:|
| 2020-02-29 00:00:00.000 |      10 |        6 |    689 |                       3006 |                0 |                     0 |                    71 |          0.19   |             0      |             0      |             0.1007 |                           |    29 |                   3710 |                   3710 |                      705 |
| 2020-02-28 00:00:00.000 |      10 |        6 |    689 |                       3006 |                0 |                    14 |                    71 |          0.19   |             0      |             0.0199 |             0.1007 |                           |    28 |                   3710 |                   3710 |                      705 |
| 2020-02-27 00:00:00.000 |      10 |        4 |    691 |                       3006 |                0 |                    14 |                    71 |          0.19   |             0      |             0.0199 |             0.1007 | last person left the ship |    27 |                   3710 |                   3710 |                      705 |
| 2020-02-26 00:00:00.000 |      10 |        4 |    691 |                       3006 |               14 |                    14 |                    84 |          0.19   |             0.0199 |             0.0199 |             0.1191 |                           |    26 |                   3652 |                   3710 |                      705 |
| 2020-02-25 00:00:00.000 |       0 |        3 |    688 |                       3020 |                0 |                    57 |                   149 |          0.1863 |             0      |             0.0825 |             0.2156 |                           |    25 |                   2945 |                   3710 |                      691 |
| 2020-02-24 00:00:00.000 |       0 |        3 |    688 |                       3020 |                0 |                    57 |                   237 |          0.1863 |             0      |             0.0825 |             0.343  |                           |    24 |                   2375 |                   3710 |                      691 |
| 2020-02-23 00:00:00.000 |       0 |        3 |    688 |                       3020 |               57 |                    57 |                   336 |          0.1863 |             0.0825 |             0.0825 |             0.4863 |                           |    23 |                   1915 |                   4247 |                      691 |
| 2020-02-22 00:00:00.000 |       1 |        2 |    631 |                       3077 |                0 |                    13 |                   349 |          0.1709 |             0      |             0.0205 |             0.5505 |                           |    22 |                   1544 |                   3193 |                      634 |
| 2020-02-21 00:00:00.000 |       1 |        2 |    631 |                       3077 |                0 |                    92 |                   416 |          0.1709 |             0      |             0.1451 |             0.6562 |                           |    21 |                   1245 |                   2401 |                      634 |
| 2020-02-20 00:00:00.000 |       1 |        2 |    631 |                       3077 |               13 |                   180 |                   459 |          0.1709 |             0.0205 |             0.2839 |             0.724  | end of quarantine         |    20 |                   1004 |                   1805 |                      634 |


Table: Date
| Date                    |   Year |   Month |   Day |   DayInt |   Week of Year |   Day in Week | Day Name   | Month Name   |   Day number |
|:------------------------|-------:|--------:|------:|---------:|---------------:|--------------:|:-----------|:-------------|-------------:|
| 2020-01-22 00:00:00.000 |   2020 |       1 |    22 | 20200122 |              4 |             3 | streda     | január       |            1 |
| 2020-01-23 00:00:00.000 |   2020 |       1 |    23 | 20200123 |              4 |             4 | štvrtok    | január       |            2 |
| 2020-01-24 00:00:00.000 |   2020 |       1 |    24 | 20200124 |              4 |             5 | piatok     | január       |            3 |
| 2020-01-25 00:00:00.000 |   2020 |       1 |    25 | 20200125 |              4 |             6 | sobota     | január       |            4 |
| 2020-01-26 00:00:00.000 |   2020 |       1 |    26 | 20200126 |              4 |             7 | nedeľa     | január       |            5 |
| 2020-01-27 00:00:00.000 |   2020 |       1 |    27 | 20200127 |              5 |             1 | pondelok   | január       |            6 |
| 2020-01-28 00:00:00.000 |   2020 |       1 |    28 | 20200128 |              5 |             2 | utorok     | január       |            7 |
| 2020-01-29 00:00:00.000 |   2020 |       1 |    29 | 20200129 |              5 |             3 | streda     | január       |            8 |
| 2020-01-30 00:00:00.000 |   2020 |       1 |    30 | 20200130 |              5 |             4 | štvrtok    | január       |            9 |
| 2020-01-31 00:00:00.000 |   2020 |       1 |    31 | 20200131 |              5 |             5 | piatok     | január       |           10 |


Table: Slicer Region Order
|   slicer n.o. | Economic Region     |   Importance |
|--------------:|:--------------------|-------------:|
|             1 | USA & Canada        |            1 |
|             2 | Australia & Oceania |            7 |
|             3 | Carribean America   |            9 |
|             4 | European Union      |            2 |
|             5 | China               |            4 |
|             6 | Asia without China  |            6 |
|             7 | South America       |           10 |
|             8 | Non EU countries    |            3 |
|             9 | Russia              |            5 |
|            10 | Africa              |            8 |


Table: WorldRegion
|   internal row ID | Country Name (usual)   | 2char country code   | 3char country code   | Economic Region     | Main country   | Global Membership   | Continent     |
|------------------:|:-----------------------|:---------------------|:---------------------|:--------------------|:---------------|:--------------------|:--------------|
|                 1 | Afghanistan            | AF                   | AFG                  | Asia without China  |                |                     | Asia          |
|                 2 | ?land Islands          | AX                   | ALA                  | Non EU countries    |                |                     | Europe        |
|                 3 | Albania                | AL                   | ALB                  | Non EU countries    |                |                     | Europe        |
|                 4 | Algeria                | DZ                   | DZA                  | Africa              |                |                     | Africa        |
|                 5 | American Samoa         | AS                   | ASM                  | Australia & Oceania |                |                     | Oceania       |
|                 6 | Andorra                | AD                   | AND                  | Non EU countries    |                |                     | Europe        |
|                 7 | Angola                 | AO                   | AGO                  | Africa              |                |                     | Africa        |
|                 8 | Anguilla               | AI                   | AIA                  | Carribean America   |                |                     | North America |
|                 9 | Antarctica             | AQ                   | ATA                  | Antarctica          |                |                     | Antarctica    |
|                10 | Antigua and Barbuda    | AG                   | ATG                  | Carribean America   |                |                     | North America |

 


tables: name: (i)_WorldmetersAPI
data: (i)_WorldmetersAPI.csv
name: (_i)_CountryNamesTranslation
data: (_i)_CountryNamesTranslation.csv
name: @Info
data: @Info.csv
name: @Last_Update
data: @Last_Update.csv
name: CDS_Infected_Deaths_Cured
data: CDS_Infected_Deaths_Cured.csv
name: CDS_Last numbers
data: CDS_Last numbers.csv
name: CountryPopulation
data: CountryPopulation.csv
name: Cruise Ship
data: Cruise Ship.csv
name: Date
data: Date.csv
name: Slicer Region Order
data: Slicer Region Order.csv
name: WorldRegion
data: WorldRegion.csv
label: CDS_Infected_Deaths_Cured
Date
Date
Date
CDS_Infected_Deaths_Cured
2char_Country_Code
WorldRegion
2char country code
CDS_Last numbers
2char_Country_Code
WorldRegion
2char country code
CountryPopulation
Country Code
WorldRegion
2char country code
WorldRegion
Economic Region
Slicer Region Order
Economic Region
(i)_WorldmetersAPI
country
CountryPopulation
Country
output: {
    "joins": [
        {
            "from_table": "CDS_Infected_Deaths_Cured",
            "from_column": "Date",
            "to_table": "Date",
            "to_column": "Date"
        },
        {
            "from_table": "CDS_Infected_Deaths_Cured",
            "from_column": "2char_Country_Code",
            "to_table": "WorldRegion",
            "to_column": "2char country code"
        },
        {
            "from_table": "CDS_Last numbers",
            "from_column": "2char_Country_Code",
            "to_table": "WorldRegion",
            "to_column": "2char country code"
        },
        {
            "from_table": "CountryPopulation",
            "from_column": "Country Code",
            "to_table": "WorldRegion",
            "to_column": "2char country code"
        },
        {
            "from_table": "WorldRegion",
            "from_column": "Economic Region",
            "to_table": "Slicer Region Order",
            "to_column": "Economic Region"
        },
        {
            "from_table": "(i)_WorldmetersAPI",
            "from_column": "country",
            "to_table": "CountryPopulation",
            "to_column": "Country"
        }
    ]
}