DataFrame'leri birleştirme

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Liam Brannigan

Data Scientist & Polars Contributor

Yorum verileri

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    |

İnceleme (inspections) veri seti

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              |

Join nedir?

Tek bir DataFrame gösteren diyagram.

Join nedir?

İki DataFrame gösteren diyagram.

Join nedir?

Eşleşen anahtar vurgulanmış iki DataFrame'i gösteren diyagram.

Join nedir?

Paylaşılan sütunlardaki eşleşen satırlara göre iki DataFrame'in birleştirildiğini gösteren diyagram.

Join nedir?

Paylaşılan sütunlardaki eşleşen satırlara göre iki DataFrame'in, eşleşen anahtar vurgulanarak birleştirildiğini gösteren diyagram.

Tek sütunda join

reviews.join(                                       )

Tek sütunda join

reviews.join(inspections,                           )

Tek sütunda join

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

Tek sütunda join

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              |

Birden çok sütunda join

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

Birden çok sütunda join

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           |

Join stratejisi seçme

2 tablo

Inner join

Inner join gösterimi

Left join

Left join gösterimi

Full join

Full join gösterimi

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