Att joina DataFrames

Datatransformation med Polars

Liam Brannigan

Data Scientist & Polars Contributor

Recensionsdata

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    |

Datamängden inspections

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              |

Vad är en join?

Diagram som visar en enskild DataFrame.

Vad är en join?

Diagram som visar två DataFrames.

Vad är en join?

Diagram som visar två DataFrames med en matchande nyckel markerad.

Vad är en join?

Diagram som visar hur två DataFrames kombineras genom att matcha rader på gemensamma kolumner.

Vad är en join?

Diagram som visar hur två DataFrames kombineras genom att matcha rader på gemensamma kolumner med en matchande nyckel markerad.

Join på en enda kolumn

reviews.join(                                       )

Join på en enda kolumn

reviews.join(inspections,                           )

Join på en enda kolumn

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

Join på en enda kolumn

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              |

Join på flera kolumner

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

Join på flera kolumner

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           |

Välja join-strategi

2 tabeller

Inner join

Illustration av inner join

Left join

Illustration av left join

Full join

Illustration av full join

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Datatransformation med Polars