Łączenie DataFrames

Transformacje danych z Polars

Liam Brannigan

Data Scientist & Polars Contributor

Dane z recenzjami

shape: (5, 4)
| business         | location    | review | price |
| ---              | ---         | ---    | ---   |
| str              | str         | f64    | i64   |
|------------------|-------------|--------|-------|
| 7burgers         | Wakey Wakey | 4.2    | 15    |
| Bang Bang Burger | Forest Rd.  | 3.8    | 12    |
| Costa Coffee     | City Point  | 4.5    | 8     |
| Costa Coffee     | Waterloo    | 4.1    | 8     |
| The Queens Head  | Denman St.  | 4.7    | 25    |

Zbiór danych z kontrolami

inspections = pl.read_csv("restaurant_inspections.csv")

shape: (5, 4)
| business        | location    | type       | hygiene_rating |
| ---             | ---         | ---        | ---            |
| str             | str         | str        | i64            |
|-----------------|-------------|------------|----------------|
| 7burgers        | Wakey Wakey | restaurant | 4              |
| Costa Coffee    | City Point  | café       | 5              |
| Costa Coffee    | Waterloo    | café       | 3              |
| The Queens Head | Denman St.  | bar        | 5              |
| Wagamama        | Soho        | restaurant | 4              |

Czym jest złączenie?

Diagram przedstawiający jeden DataFrame.

Czym jest złączenie?

Diagram przedstawiający dwa DataFrames.

Czym jest złączenie?

Diagram przedstawiający dwa DataFrames z wyróżnionym wspólnym kluczem.

Czym jest złączenie?

Diagram przedstawiający łączenie dwóch DataFrames przez dopasowanie wierszy na wspólnych kolumnach.

Czym jest złączenie?

Diagram przedstawiający łączenie dwóch DataFrames przez dopasowanie wierszy na wspólnych kolumnach z wyróżnionym kluczem.

Złączenie po jednej kolumnie

reviews.join(                                       )

Złączenie po jednej kolumnie

reviews.join(inspections,                           )

Złączenie po jednej kolumnie

reviews.join(inspections, on="business"             )

Złączenie po jednej kolumnie

reviews.join(inspections, on="business", how="inner")

shape: (6, 7)
| business      | location    | ... | location_right | hygiene_rating |
| ---           | ---         | ... | ---            | ---            |
| str           | str         | ... | str            | i64            |
|---------------|-------------|-----|----------------|----------------|
| 7burgers      | Wakey Wakey | ... | Wakey Wakey    | 4              |
| Costa Coffee  | City Point  | ... | City Point     | 5              |
| Costa Coffee  | Waterloo    | ... | City Point     | 5              |
| Costa Coffee  | City Point  | ... | Waterloo       | 3              |
| Costa Coffee  | Waterloo    | ... | Waterloo       | 3              |
| The Queens Hd | Denman St.  | ... | Denman St.     | 5              |

Złączenie po wielu kolumnach

reviews.join(inspections, on=["business", "location"])

Złączenie po wielu kolumnach

reviews.join(inspections, on=["business", "location"])

shape: (4, 6)
| business        | location    | review | price | type       | hygiene_rating |
| ---             | ---         | ---    | ---   | ---        | ---            |
| str             | str         | f64    | i64   | str        | i64            |
|-----------------|-------------|--------|-------|------------|----------------|
| 7burgers        | Wakey Wakey | 4.2    | 15    | restaurant | 4              |
| Costa Coffee    | City Point  | 4.5    | 8     | café       | 5              |
| Costa Coffee    | Waterloo    | 4.1    | 8     | café       | 3              |
| The Queens Head | Denman St.  | 4.7    | 25    | bar        | 5              |

Left join

reviews.join(inspections, on=["business", "location"],           )

Left join

reviews.join(inspections, on=["business", "location"], how="left")

shape: (5, 6)
| business         | location    | review | price | type       | hygiene_rating |
| ---              | ---         | ---    | ---   | ---        | ---            |
| str              | str         | f64    | i64   | str        | i64            |
|------------------|-------------|--------|-------|------------|----------------|
| 7burgers         | Wakey Wakey | 4.2    | 15    | restaurant | 4              |
| Bang Bang Burger | Forest Rd.  | 3.8    | 12    | null       | null           |
| Costa Coffee     | City Point  | 4.5    | 8     | café       | 5              |
| Costa Coffee     | Waterloo    | 4.1    | 8     | café       | 3              |
| The Queens Head  | Denman St.  | 4.7    | 25    | bar        | 5              |

Full join

reviews.join(inspections, on=["business", "location"],                          )

Full join

reviews.join(inspections, on=["business", "location"], how="full"               )

Full join

reviews.join(inspections, on=["business", "location"], how="full", coalesce=True)

shape: (6, 6)
| business         | location    | review | price | type       | hygiene_rating |
| ---              | ---         | ---    | ---   | ---        | ---            |
| str              | str         | f64    | i64   | str        | i64            |
|------------------|-------------|--------|-------|------------|----------------|
| 7burgers         | Wakey Wakey | 4.2    | 15    | restaurant | 4              |
| Costa Coffee     | City Point  | 4.5    | 8     | café       | 5              |
| Costa Coffee     | Waterloo    | 4.1    | 8     | café       | 3              |
| The Queens Head  | Denman St.  | 4.7    | 25    | bar        | 5              |
| Wagamama         | Soho        | null   | null  | restaurant | 4              |
| Bang Bang Burger | Forest Rd.  | 3.8    | 12    | null       | null           |

Jak wybrać rodzaj złączenia?

2 tabele

Inner join

Schemat złączenia inner join

Left join

Schemat złączenia left join

Full join

Schemat złączenia full join

Czas na praktykę!

Transformacje danych z Polars