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: Abfrage1
|     id | title                      | overview                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |   popularity |   revenue | posterPath                       | releaseDate   |   voteAvg |   voteCount |   runtime | tagline                               |
|-------:|:---------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------:|----------:|:---------------------------------|:--------------|----------:|------------:|----------:|:--------------------------------------|
|  20982 | Naruto Shippuden the Movie | Demons that once almost destroyed the world, are revived by someone. To prevent the world from being destroyed, the demon has to be sealed and the only one who can do it is the shrine maiden Shion from the country of demons, who has two powers; one is sealing demons and the other is predicting the deaths of humans. This time Naruto's mission is to guard Shion, but she predicts Naruto's death. The only way to escape it, is to get away from Shion, which would leave her unguarded, then the demon, whose only goal is to kill Shion will do so, thus meaning the end of the world. Naruto decides to challenge this "prediction of death." |      296.707 |         0 | /vDkct38sSFSWJIATlfJw0l3QOIR.jpg | 2007-08-04    |       7.1 |         321 |        94 |                                       |
|  40170 | Mortal Kombat: Rebirth     | MORTAL KOMBAT: REBIRTH is a short film released by Kevin Tancharoen (Director) in 2010. It was originally made as a proof of concept for Tancharoen's pitch to Warner Brothers for a reboot movie franchise. This 8-minute short features an intricate fight scene choreographed by Larnell Stovall. It also reintroduces classic Mortal Kombat characters, including: Jax (Michael Jai White), Sonya Blade (Jeri Ryan), Johnny Cage (Matt Mullins), Scorpion (Ian Anthony Dale), Baraka (Lateef Crowder) and Shang Tsung (James Lew).                                                                                                                     |      280.737 |         0 | /78JIw8JICcPKDIURCJJq2F43iIZ.jpg | 2010-06-08    |       7   |          85 |         8 |                                       |
|  62717 | Loki - Arnaldo Baptista    | Loki brings the trajectory of Arnaldo Baptista from childhood, passing through the most successful phase as leader of the Mutantes, marriage to singer Rita Lee and then separation. He also goes through the depression that devastated his life after the group ended and that led him to attempt suicide, his solo career, rapprochement with his brother and member of the Mutantes, Sérgio Dias, culminating in the band's return in 2006.                                                                                                                                                                                                            |      341.279 |         0 | /cYl39kCMjP37e39CbJqxWHvf1ez.jpg | 2008-10-17    |       6.9 |           9 |       120 |                                       |
| 317442 | The Last: Naruto the Movie | Two years after the events of the Fourth Great Ninja War, the moon that Hagoromo Otsutsuki created long ago to seal away the Gedo Statue begins to descend towards the world, threatening to become a meteor that would destroy everything on impact. Amidst this crisis, a direct descendant of Kaguya Otsutsuki named Toneri Otsutsuki attempts to kidnap Hinata Hyuga but ends up abducting her younger sister Hanabi. Naruto and his allies now mount a rescue mission before finding themselves embroiled in a final battle to decide the fate of everything.                                                                                         |      250.033 |         0 | /bAQ8O5Uw6FedtlCbJTutenzPVKd.jpg | 2014-12-06    |       7.8 |         929 |       114 |                                       |
| 347201 | Boruto: Naruto the Movie   | Boruto is the son of the 7th Hokage Naruto who completely rejects his father. Behind this, he has feelings of wanting to surpass Naruto, who is respected as a hero. He ends up meeting his father's friend Sasuke, and requests to become... his apprentice!? The curtain on the story of the new generation written by Masashi Kishimoto rises!                                                                                                                                                                                                                                                                                                          |      266.157 |         0 | /1k6iwC4KaPvTBt1JuaqXy3noZRY.jpg | 2015-08-07    |       7.7 |         785 |       100 | Forge your own path.                  |
| 379686 | Space Jam: A New Legacy    | When LeBron and his young son Dom are trapped in a digital space by a rogue A.I., LeBron must get them home safe by leading Bugs, Lola Bunny and the whole gang of notoriously undisciplined Looney Tunes to victory over the A.I.'s digitized champions on the court. It's Tunes versus Goons in the highest-stakes challenge of his life.                                                                                                                                                                                                                                                                                                                |      228.829 |         0 | /boATtcBEjJF7z3HEyWCCpBqRDs4.jpg | 2021-07-08    |       0   |           0 |         0 | Welcome to the Jam!                   |
| 385687 | Fast & Furious 10          | The penultimate installment of the Fast and Furious franchise.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |      537.376 |         0 | /2DyEk84XnbJEdPlGF43crxfdtHH.jpg |               |       0   |           0 |         0 |                                       |
| 412656 | Chaos Walking              | Two unlikely companions embark on a perilous adventure through the badlands of an unexplored planet as they try to escape a dangerous and disorienting reality, where all inner thoughts are seen and heard by everyone.                                                                                                                                                                                                                                                                                                                                                                                                                                   |      407.914 |         0 | /9kg73Mg8WJKlB9Y2SAJzeDKAnuB.jpg | 2021-02-24    |       7   |         731 |       109 | No one escapes the noise.             |
| 471498 | Oxygen                     | A woman wakes in a cryogenic chamber with no recollection of how she got there, and must find a way out before running out of air.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         |      235.304 |         0 | /u74DFoZGTcZ8cuHO8nvQkCqXEVP.jpg | 2021-05-12    |       6.7 |         559 |       100 | No escape. No memory. 90 min to live. |
| 484718 | Coming 2 America           | Prince Akeem Joffer is set to become King of Zamunda when he discovers he has a son he never knew about in America – a street savvy Queens native named Lavelle. Honoring his royal father's dying wish to groom this son as the crown prince, Akeem and Semmi set off to America once again.                                                                                                                                                                                                                                                                                                                                                              |      224.236 |         0 | /nWBPLkqNApY5pgrJFMiI9joSI30.jpg | 2021-03-05    |       6.8 |        1364 |       110 | A sequel is in the heir.              |


Table: Abfrage3
|   weekNr |   cases-recovered-deaths |
|---------:|-------------------------:|
|       15 |                   298889 |
|       16 |                   313802 |
|       17 |                   312229 |
|       18 |                   282379 |
|       19 |                   229475 |
|       20 |                   173999 |
|       21 |                   118808 |
|       22 |                    70408 |
|       23 |                    57774 |


Table: Covid
| cases-LAG(cases) OVER (ORDER BY weekNr ASC)   | deaths-LAG(deaths) OVER (ORDER BY weekNr ASC)   | recovered-LAG(recovered) OVER (ORDER BY weekNr ASC)   |   weekNr | concat("KW ", weekNr)   |
|:----------------------------------------------|:------------------------------------------------|:------------------------------------------------------|---------:|:------------------------|
|                                               |                                                 |                                                       |       15 | KW 15                   |
| 122298                                        | 1038                                            | 106347                                                |       16 | KW 16                   |
| 129847                                        | 1592                                            | 129828                                                |       17 | KW 17                   |
| 106656                                        | 1555                                            | 134951                                                |       18 | KW 18                   |
| 77072                                         | 1378                                            | 128598                                                |       19 | KW 19                   |
| 57825                                         | 1283                                            | 112018                                                |       20 | KW 20                   |
| 36892                                         | 1105                                            | 90978                                                 |       21 | KW 21                   |
| 33855                                         | 530                                             | 81725                                                 |       22 | KW 22                   |
| 1440                                          | 857                                             | 13217                                                 |       23 | KW 23                   |


Table: CovidAsStrings
|   weekNr | cases      | deaths   | recovered   |
|---------:|:-----------|:---------|:------------|
|       15 |            |          |             |
|       16 | 122.3 Tsd. | 1038     | 106.3 Tsd.  |
|       17 | 129.8 Tsd. | 1592     | 129.8 Tsd.  |
|       18 | 106.7 Tsd. | 1555     | 135.0 Tsd.  |
|       19 | 77.1 Tsd.  | 1378     | 128.6 Tsd.  |
|       20 | 57.8 Tsd.  | 1283     | 112.0 Tsd.  |
|       21 | 36.9 Tsd.  | 1105     | 91.0 Tsd.   |
|       22 | 33.9 Tsd.  | 530      | 81.7 Tsd.   |
|       23 | 1.4 Tsd.   | 857      | 13.2 Tsd.   |


Table: Location
| Titel                             | countryId   | cname                    |   weekNr |   Popularität |   movieId | AnzahlTrends   |
|:----------------------------------|:------------|:-------------------------|---------:|--------------:|----------:|:---------------|
| Our Friend                        | US          | United States of America |       16 |       201.468 |    583903 |                |
| Grand Isle                        | US          | United States of America |       16 |       201.706 |    560192 |                |
| Fast & Furious 10                 | US          | United States of America |       16 |       204.437 |    385687 |                |
| Venom                             | US          | United States of America |       16 |       204.586 |    335983 |                |
| Captain Marvel                    | US          | United States of America |       16 |       204.95  |    299537 |                |
| Underwater                        | US          | United States of America |       16 |       205.846 |    443791 |                |
| John Wick: Chapter 3 - Parabellum | US          | United States of America |       16 |       209.898 |    458156 |                |
| Mulan                             | US          | United States of America |       16 |       211.638 |    337401 |                |
| Alone                             | US          | United States of America |       16 |       212.237 |    509635 |                |
| 6 Underground                     | US          | United States of America |       16 |       214.284 |    509967 |                |


Table: MovieCountryTrendWeek
|   weekNr |   popularity | title                                  | Land                     | ISO_ID   |
|---------:|-------------:|:---------------------------------------|:-------------------------|:---------|
|       16 |      215.62  | Terminator: Dark Fate                  | United States of America | US       |
|       16 |     1023.77  | Monster Hunter                         | United States of America | US       |
|       16 |      204.437 | Fast & Furious 10                      | United States of America | US       |
|       16 |     2163.72  | The Marksman                           | United States of America | US       |
|       16 |      220.704 | Nomadland                              | United States of America | US       |
|       16 |     4459.3   | Godzilla vs. Kong                      | United States of America | US       |
|       16 |      204.95  | Captain Marvel                         | United States of America | US       |
|       16 |      280.737 | Mortal Kombat: Rebirth                 | United States of America | US       |
|       16 |      322.291 | The SpongeBob Movie: Sponge on the Run | United States of America | US       |
|       16 |     3500.81  | Mortal Kombat                          | United States of America | US       |


Table: MovieGenres_Popularity
|   weekNr |   genreId |   AnzahlTrends | Genre           |   Popularität |
|---------:|----------:|---------------:|:----------------|--------------:|
|       16 |        28 |             56 | Action          |      40674.7  |
|       16 |        53 |             34 | Thriller        |      21952.6  |
|       16 |        12 |             30 | Adventure       |      21362.6  |
|       16 |        14 |             29 | Fantasy         |      22090.4  |
|       16 |        18 |             25 | Drama           |      11865.8  |
|       16 |        35 |             24 | Comedy          |      11091.3  |
|       16 |       878 |             22 | Science Fiction |      18545.3  |
|       16 |        16 |             19 | Animation       |      10781.1  |
|       16 |        80 |             18 | Crime           |      12139.6  |
|       16 |     10751 |             14 | Family          |       6778.99 |


Table: movieratings covid
|   weekNr |       cases |   deaths |   recovered |
|---------:|------------:|---------:|------------:|
|       15 | 3.15556e+06 |    81111 | 2.77556e+06 |
|       16 | 3.27785e+06 |    82149 | 2.8819e+06  |
|       17 | 3.4077e+06  |    83741 | 3.01173e+06 |
|       18 | 3.51436e+06 |    85296 | 3.14668e+06 |
|       19 | 3.59143e+06 |    86674 | 3.27528e+06 |
|       20 | 3.64925e+06 |    87957 | 3.3873e+06  |
|       21 | 3.68614e+06 |    89062 | 3.47828e+06 |
|       22 | 3.72e+06    |    89592 | 3.56e+06    |
|       23 | 3.72144e+06 |    90449 | 3.57322e+06 |


Table: MovieTrendAge
|   weekNr | agegroups   |   count(*) |
|---------:|:------------|-----------:|
|       16 | 0-19        |         22 |
|       16 | 20-29       |         77 |
|       16 | 30-39       |        143 |
|       16 | 40-49       |        176 |
|       16 | 50-59       |        188 |
|       16 | 60-69       |         84 |
|       16 | 70-79       |         26 |
|       16 | 80<         |         11 |
|       17 | 0-19        |          9 |
|       17 | 20-29       |         73 |


Table: MovieTrendsCountry
|   weekNr |   AnzahlTrends | Land        | ISO_ID   |
|---------:|---------------:|:------------|:---------|
|       16 |              1 | Belgium     | BE       |
|       16 |              1 | Chile       | CL       |
|       16 |              1 | Cyprus      | CY       |
|       16 |              1 | Hungary     | HU       |
|       16 |              1 | Lithuania   | LT       |
|       16 |              1 | Netherlands | NL       |
|       16 |              1 | Russia      | RU       |
|       16 |              1 | Sweden      | SE       |
|       16 |              1 | Thailand    | TH       |
|       17 |              1 | Bolivia     | BO       |


Table: MovieTrendsGender
|   weekNr |   count(*) |   gender |
|---------:|-----------:|---------:|
|       16 |        170 |        0 |
|       16 |        278 |        1 |
|       16 |        694 |        2 |
|       16 |          2 |        3 |
|       17 |        182 |        0 |
|       17 |        267 |        1 |
|       17 |        678 |        2 |
|       17 |          2 |        3 |
|       18 |        190 |        0 |
|       18 |        259 |        1 |


Table: MWP
|   weekNr |   movieId | title                                     |   voteAvg |   popularity |   voteCount |
|---------:|----------:|:------------------------------------------|----------:|-------------:|------------:|
|       16 |    399566 | Godzilla vs. Kong                         |       8.2 |      4459.3  |        4848 |
|       16 |    460465 | Mortal Kombat                             |       8.2 |      3500.81 |         741 |
|       16 |    615678 | Thunder Force                             |       5.8 |      2556.11 |         404 |
|       16 |    791373 | Zack Snyder's Justice League              |       8.5 |      2375.45 |        5096 |
|       16 |    634528 | The Marksman                              |       7.1 |      2163.72 |         149 |
|       16 |    615457 | Nobody                                    |       8.5 |      1931.29 |         689 |
|       16 |    412656 | Chaos Walking                             |       7.4 |      1656.47 |         436 |
|       16 |    632357 | The Unholy                                |       5.5 |      1619.63 |          43 |
|       16 |    527774 | Raya and the Last Dragon                  |       8.3 |      1432.34 |        2399 |
|       16 |    664767 | Mortal Kombat Legends: Scorpion's Revenge |       8.4 |      1221.54 |         863 |


Table: SeriesGenres_Popularity
|   weekNr |   genreId |   Popularität |   AnzahlTrends | Genre              |
|---------:|----------:|--------------:|---------------:|:-------------------|
|       16 |        18 |     29931.3   |             72 | Drama              |
|       16 |     10765 |     16974.1   |             35 | Sci-Fi & Fantasy   |
|       16 |     10759 |     16184     |             35 | Action & Adventure |
|       16 |        80 |      7263.41  |             24 | Crime              |
|       16 |      9648 |      6010.43  |             19 | Mystery            |
|       16 |     10768 |      5315.73  |              2 | War & Politics     |
|       16 |        16 |      4520.35  |             14 | Animation          |
|       16 |        35 |      2995.68  |             15 | Comedy             |
|       16 |     10766 |      1336.36  |              6 | Soap               |
|       16 |     10762 |       947.965 |              3 | Kids               |


Table: SeriesTrendAge
|   weekNr |   InSeries | agegroups   |
|---------:|-----------:|:------------|
|       16 |         62 | 0-19        |
|       16 |        190 | 20-29       |
|       16 |        186 | 30-39       |
|       16 |        128 | 40-49       |
|       16 |         48 | 50-59       |
|       16 |         14 | 60-69       |
|       16 |          4 | 70-79       |
|       16 |          4 | 80<         |
|       17 |         59 | 0-19        |
|       17 |        184 | 20-29       |


Table: SeriesTrendsCountry
|   weekNr |   AnzahlTrends | Land           | ISO_ID   |
|---------:|---------------:|:---------------|:---------|
|       16 |              3 | Argentina      | AR       |
|       16 |              5 | Canada         | CA       |
|       16 |              3 | Colombia       | CO       |
|       16 |              2 | Germany        | DE       |
|       16 |              4 | Spain          | ES       |
|       16 |              1 | France         | FR       |
|       16 |              4 | United Kingdom | GB       |
|       16 |              1 | Ireland        | IE       |
|       16 |              1 | Italy          | IT       |
|       16 |              8 | Japan          | JP       |


Table: SeriesTrendsGender
|   weekNr |   count(*) |   gender |
|---------:|-----------:|---------:|
|       16 |        205 |        0 |
|       16 |        311 |        1 |
|       16 |        495 |        2 |
|       16 |          1 |        3 |
|       17 |        204 |        0 |
|       17 |        303 |        1 |
|       17 |        504 |        2 |
|       17 |          1 |        3 |
|       18 |        201 |        0 |
|       18 |        285 |        1 |


Table: SWP
|   weekNr |   seriesId | title                |   voteAvg |   popularity |   voteCount |
|---------:|-----------:|:---------------------|----------:|-------------:|------------:|
|       16 |       1416 | Grey's Anatomy       |       8.2 |     1016.61  |        5905 |
|       16 |      76669 | Elite                |       8.2 |      313.803 |        6304 |
|       16 |       1622 | Supernatural         |       8.2 |      272.073 |        5035 |
|       16 |       4604 | Smallville           |       8.2 |      263.146 |        2365 |
|       16 |     104877 | You Knock on My Door |       8.2 |      253.201 |         229 |
|       16 |      76773 | Station 19           |       8.2 |      223.366 |         781 |
|       16 |      60797 | Scorpion             |       8.2 |      223.169 |        2290 |
|       16 |      12971 | Dragon Ball Z        |       8.2 |      220.251 |        2232 |
|       16 |       4057 | Criminal Minds       |       8.2 |      189.969 |        2281 |
|       16 |      16286 | Yo soy Betty, la fea |       8.2 |      173.603 |        2003 |


Table: Top2MovieGenders
|   weekNr |   popularity | title             |   gender |   count(*) | geschlecht   |
|---------:|-------------:|:------------------|---------:|-----------:|:-------------|
|       16 |      3500.81 | Mortal Kombat     |        0 |          1 | unbekannt    |
|       16 |      3500.81 | Mortal Kombat     |        1 |          1 | weiblich     |
|       16 |      3500.81 | Mortal Kombat     |        2 |         10 | männlich     |
|       17 |      3086.89 | Godzilla vs. Kong |        1 |          4 | weiblich     |
|       17 |      3086.89 | Godzilla vs. Kong |        2 |          8 | männlich     |
|       18 |      2341.55 | Godzilla vs. Kong |        1 |          4 | weiblich     |
|       18 |      2341.55 | Godzilla vs. Kong |        2 |          8 | männlich     |
|       19 |      2747.43 | Mortal Kombat     |        0 |          1 | unbekannt    |
|       19 |      2747.43 | Mortal Kombat     |        1 |          1 | weiblich     |
|       19 |      2747.43 | Mortal Kombat     |        2 |         10 | männlich     |


Table: Top2SeriesGender
|   weekNr |   popularity | title                             |   gender |   count(*) | geschlecht   |
|---------:|-------------:|:----------------------------------|---------:|-----------:|:-------------|
|       16 |     1704.74  | The Good Doctor                   |        1 |          4 | weiblich     |
|       16 |     1704.74  | The Good Doctor                   |        2 |          5 | männlich     |
|       17 |     1462.94  | The Good Doctor                   |        1 |          4 | weiblich     |
|       17 |     1462.94  | The Good Doctor                   |        2 |          5 | männlich     |
|       18 |     1727.11  | The Falcon and the Winter Soldier |        0 |          3 | unbekannt    |
|       18 |     1727.11  | The Falcon and the Winter Soldier |        1 |          5 | weiblich     |
|       18 |     1727.11  | The Falcon and the Winter Soldier |        2 |          8 | männlich     |
|       19 |      879.932 | The Flash                         |        0 |          6 | unbekannt    |
|       19 |      879.932 | The Flash                         |        1 |          5 | weiblich     |
|       19 |      879.932 | The Flash                         |        2 |          5 | männlich     |


Table: Top3MovieGenders
|   weekNr |   popularity | title                                                  |   gender |   count(*) | geschlecht   |
|---------:|-------------:|:-------------------------------------------------------|---------:|-----------:|:-------------|
|       16 |      2556.11 | Thunder Force                                          |        0 |          2 | unbekannt    |
|       16 |      2556.11 | Thunder Force                                          |        1 |          6 | weiblich     |
|       16 |      2556.11 | Thunder Force                                          |        2 |          4 | männlich     |
|       17 |      2777.87 | Demon Slayer -Kimetsu no Yaiba- The Movie: Mugen Train |        1 |          2 | weiblich     |
|       17 |      2777.87 | Demon Slayer -Kimetsu no Yaiba- The Movie: Mugen Train |        2 |         10 | männlich     |
|       18 |      1971.55 | Nobody                                                 |        1 |          2 | weiblich     |
|       18 |      1971.55 | Nobody                                                 |        2 |         10 | männlich     |
|       19 |      1979.64 | Vanquish                                               |        0 |          1 | unbekannt    |
|       19 |      1979.64 | Vanquish                                               |        1 |          3 | weiblich     |
|       19 |      1979.64 | Vanquish                                               |        2 |          8 | männlich     |


Table: Top3SeriesGender
|   weekNr |   popularity | title           |   gender |   count(*) | geschlecht   |
|---------:|-------------:|:----------------|---------:|-----------:|:-------------|
|       16 |      1423.81 | The Flash       |        0 |          6 | unbekannt    |
|       16 |      1423.81 | The Flash       |        1 |          5 | weiblich     |
|       16 |      1423.81 | The Flash       |        2 |          5 | männlich     |
|       17 |      1245.7  | The Flash       |        0 |          6 | unbekannt    |
|       17 |      1245.7  | The Flash       |        1 |          5 | weiblich     |
|       17 |      1245.7  | The Flash       |        2 |          5 | männlich     |
|       18 |      1293.39 | The Flash       |        0 |          6 | unbekannt    |
|       18 |      1293.39 | The Flash       |        1 |          5 | weiblich     |
|       18 |      1293.39 | The Flash       |        2 |          5 | männlich     |
|       19 |       870.23 | The Good Doctor |        1 |          4 | weiblich     |


Table: TopMovie
|   weekNr |   movieId | title                        |     max | GROUP_CONCAT(g.genre SEPARATOR ', ')                  | concat(mwp.voteAvg, "/10")   |
|---------:|----------:|:-----------------------------|--------:|:------------------------------------------------------|:-----------------------------|
|       16 |    399566 | Godzilla vs. Kong            | 4459.3  | Action, Science Fiction                               | 8.2/10                       |
|       17 |    460465 | Mortal Kombat                | 6983.02 | Adventure, Fantasy, Action, Thriller, Science Fiction | 7.9/10                       |
|       18 |    460465 | Mortal Kombat                | 4870.2  | Adventure, Fantasy, Action, Thriller, Science Fiction | 7.8/10                       |
|       19 |    567189 | Tom Clancy's Without Remorse | 4918.31 | Adventure, Action, Thriller, War                      | 7.3/10                       |
|       20 |    460465 | Mortal Kombat                | 2112.76 | Adventure, Fantasy, Action, Thriller, Science Fiction | 7.6/10                       |
|       21 |    632357 | The Unholy                   | 5972.41 | Horror                                                | 7.2/10                       |
|       22 |    337404 | Cruella                      | 6077.17 | Comedy, Crime                                         | 8.7/10                       |
|       23 |    337404 | Cruella                      | 5055.01 | Comedy, Crime                                         | 8.7/10                       |


Table: TopMovieGenders
|   weekNr |   popularity | title                        |   gender |   count(*) | geschlecht   |
|---------:|-------------:|:-----------------------------|---------:|-----------:|:-------------|
|       16 |      4459.3  | Godzilla vs. Kong            |        1 |          4 | weiblich     |
|       16 |      4459.3  | Godzilla vs. Kong            |        2 |          8 | männlich     |
|       17 |      6983.02 | Mortal Kombat                |        0 |          1 | unbekannt    |
|       17 |      6983.02 | Mortal Kombat                |        1 |          1 | weiblich     |
|       17 |      6983.02 | Mortal Kombat                |        2 |         10 | männlich     |
|       18 |      4870.2  | Mortal Kombat                |        0 |          1 | unbekannt    |
|       18 |      4870.2  | Mortal Kombat                |        1 |          1 | weiblich     |
|       18 |      4870.2  | Mortal Kombat                |        2 |         10 | männlich     |
|       19 |      4918.31 | Tom Clancy's Without Remorse |        0 |          1 | unbekannt    |
|       19 |      4918.31 | Tom Clancy's Without Remorse |        1 |          4 | weiblich     |


Table: TopPersonWeekGender
|   weekNr |   gender | name                       | Job            |
|---------:|---------:|:---------------------------|:---------------|
|       16 |        2 | Jason Statham              | Schauspieler   |
|       16 |        1 | Scarlett Johansson         | Schauspielerin |
|       17 |        2 | Keanu Reeves               | Schauspieler   |
|       17 |        1 | Scarlett Johansson         | Schauspielerin |
|       18 |        2 | Jason Statham              | Schauspieler   |
|       18 |        1 | Scarlett Johansson         | Schauspielerin |
|       19 |        2 | Philippe Leroy             | Schauspieler   |
|       19 |        1 | Scarlett Johansson         | Schauspielerin |
|       20 |        2 | Ángel 'Angelito' Rodríguez | Crew           |
|       20 |        1 | Angelina Jolie             | Schauspielerin |


Table: TopSeries
|   weekNr |   seriesId | title                             |     max | GROUP_CONCAT(g.genre SEPARATOR ', ')                        | concat(swp.voteAvg,"/10")   |
|---------:|-----------:|:----------------------------------|--------:|:------------------------------------------------------------|:----------------------------|
|       16 |      88396 | The Falcon and the Winter Soldier | 5146.16 | Drama, Action & Adventure, Sci-Fi & Fantasy, War & Politics | 7.9/10                      |
|       17 |      88396 | The Falcon and the Winter Soldier | 2580.79 | Drama, Action & Adventure, Sci-Fi & Fantasy, War & Politics | 7.9/10                      |
|       18 |      95557 | Invincible                        | 1885.16 | Animation, Drama, Action & Adventure                        | 8.9/10                      |
|       19 |      88396 | The Falcon and the Winter Soldier | 1013.58 | Drama, Action & Adventure, Sci-Fi & Fantasy, War & Politics | 7.9/10                      |
|       20 |     120168 | Who Killed Sara?                  | 1527.66 | Drama, Crime, Mystery                                       | 7.8/10                      |
|       21 |      63174 | Lucifer                           | 1461.07 | Crime, Sci-Fi & Fantasy                                     | 8.5/10                      |
|       22 |      63174 | Lucifer                           | 1464.51 | Crime, Sci-Fi & Fantasy                                     | 8.5/10                      |
|       23 |      84958 | Loki                              | 1926.33 | Drama, Crime, Action & Adventure, Sci-Fi & Fantasy          | 8.2/10                      |


Table: TopSeriesGender
|   weekNr |   popularity | title                             |   gender |   count(*) | geschlecht   |
|---------:|-------------:|:----------------------------------|---------:|-----------:|:-------------|
|       16 |      5146.16 | The Falcon and the Winter Soldier |        0 |          3 | unbekannt    |
|       16 |      5146.16 | The Falcon and the Winter Soldier |        1 |          5 | weiblich     |
|       16 |      5146.16 | The Falcon and the Winter Soldier |        2 |          8 | männlich     |
|       17 |      2580.79 | The Falcon and the Winter Soldier |        0 |          3 | unbekannt    |
|       17 |      2580.79 | The Falcon and the Winter Soldier |        1 |          5 | weiblich     |
|       17 |      2580.79 | The Falcon and the Winter Soldier |        2 |          8 | männlich     |
|       18 |      1885.16 | Invincible                        |        0 |          2 | unbekannt    |
|       18 |      1885.16 | Invincible                        |        1 |          2 | weiblich     |
|       18 |      1885.16 | Invincible                        |        2 |          7 | männlich     |
|       19 |      1013.58 | The Falcon and the Winter Soldier |        0 |          3 | unbekannt    |


Table: TrendsAgeGroupsWeek
|   weekNr |   weekNr2 |   count |   InSeries | agegroups   |
|---------:|----------:|--------:|-----------:|:------------|
|       16 |        16 |      22 |         62 | 0-19        |
|       16 |        16 |      77 |        190 | 20-29       |
|       16 |        16 |     143 |        186 | 30-39       |
|       16 |        16 |     176 |        128 | 40-49       |
|       16 |        16 |     188 |         48 | 50-59       |
|       16 |        16 |      84 |         14 | 60-69       |
|       16 |        16 |      26 |          4 | 70-79       |
|       16 |        16 |      11 |          4 | 80<         |
|       17 |        17 |       9 |         59 | 0-19        |
|       17 |        17 |      73 |        184 | 20-29       |

 


tables: name: Abfrage1
data: Abfrage1.csv
name: Abfrage3
data: Abfrage3.csv
name: Covid
data: Covid.csv
name: CovidAsStrings
data: CovidAsStrings.csv
name: Location
data: Location.csv
name: MovieCountryTrendWeek
data: MovieCountryTrendWeek.csv
name: MovieGenres_Popularity
data: MovieGenres_Popularity.csv
name: movieratings covid
data: movieratings covid.csv
name: MovieTrendAge
data: MovieTrendAge.csv
name: MovieTrendsCountry
data: MovieTrendsCountry.csv
name: MovieTrendsGender
data: MovieTrendsGender.csv
name: MWP
data: MWP.csv
name: SeriesGenres_Popularity
data: SeriesGenres_Popularity.csv
name: SeriesTrendAge
data: SeriesTrendAge.csv
name: SeriesTrendsCountry
data: SeriesTrendsCountry.csv
name: SeriesTrendsGender
data: SeriesTrendsGender.csv
name: SWP
data: SWP.csv
name: Top2MovieGenders
data: Top2MovieGenders.csv
name: Top2SeriesGender
data: Top2SeriesGender.csv
name: Top3MovieGenders
data: Top3MovieGenders.csv
name: Top3SeriesGender
data: Top3SeriesGender.csv
name: TopMovie
data: TopMovie.csv
name: TopMovieGenders
data: TopMovieGenders.csv
name: TopPersonWeekGender
data: TopPersonWeekGender.csv
name: TopSeries
data: TopSeries.csv
name: TopSeriesGender
data: TopSeriesGender.csv
name: TrendsAgeGroupsWeek
data: TrendsAgeGroupsWeek.csv
label: Covid
weekNr
movieratings covid
weekNr
Abfrage3
weekNr
movieratings covid
weekNr
MWP
weekNr
Covid
weekNr
SWP
weekNr
Covid
weekNr
TopSeries
weekNr
Covid
weekNr
Covid
weekNr
TopMovie
weekNr
MovieGenres_Popularity
weekNr
Covid
weekNr
SeriesGenres_Popularity
weekNr
Covid
weekNr
MovieTrendsGender
weekNr
Covid
weekNr
SeriesTrendsGender
weekNr
Covid
weekNr
MovieTrendsCountry
weekNr
Covid
weekNr
SeriesTrendsCountry
weekNr
Covid
weekNr
Covid
weekNr
CovidAsStrings
weekNr
MovieCountryTrendWeek
weekNr
Covid
weekNr
Location
weekNr
Covid
weekNr
MovieTrendAge
weekNr
Covid
weekNr
TopPersonWeekGender
weekNr
Covid
weekNr
SeriesTrendAge
weekNr
Covid
weekNr
TrendsAgeGroupsWeek
weekNr
Covid
weekNr
TopMovieGenders
weekNr
Covid
weekNr
TopSeriesGender
weekNr
Covid
weekNr
Top2MovieGenders
weekNr
Covid
weekNr
Top3MovieGenders
weekNr
Covid
weekNr
Top2SeriesGender
weekNr
Covid
weekNr
Top3SeriesGender
weekNr
Covid
weekNr
output: {
    "joins": [
        {
            "from_table": "Covid",
            "from_column": "weekNr",
            "to_table": "movieratings covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Abfrage3",
            "from_column": "weekNr",
            "to_table": "movieratings covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "MWP",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SWP",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "TopSeries",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Covid",
            "from_column": "weekNr",
            "to_table": "TopMovie",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieGenres_Popularity",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SeriesGenres_Popularity",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieTrendsGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SeriesTrendsGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieTrendsCountry",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SeriesTrendsCountry",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Covid",
            "from_column": "weekNr",
            "to_table": "CovidAsStrings",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieCountryTrendWeek",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Location",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieTrendAge",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "TopPersonWeekGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SeriesTrendAge",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "TrendsAgeGroupsWeek",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "TopMovieGenders",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "TopSeriesGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Top2MovieGenders",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Top3MovieGenders",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Top2SeriesGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Top3SeriesGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        }
    ]
}