Nettoyer des données textuelles
Transformation de données avec Polars
Liam Brannigan
Data Scientist & Polars Contributor
Rencontrez votre instructeur
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- Liam Brannigan, Lead Data Scientist
- Spécialiste ML et Data Engineering
- Contributeur Polars
Moteur de transformation
Ce cours est-il pour vous ?
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- Créer un DataFrame Polars
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- Utiliser une expression Polars
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- Effectuer une agrégation group-by
Chapitre 1
Chapitre 2
Chapitre 3
Chapitre 4
Découvrez notre jeu de données
import polars as pl
ratings = pl.read_csv("restaurant_ratings.csv")
shape: (5, 5)
| business | location | type | rating | capacity |
| --- | --- | --- | --- | --- |
| str | str | str | f64 | f64 |
|------------------|--------------|------------|--------|----------|
| 7burgers | Wakey Wakey | restaurant | 5.0 | 55.0 |
| Bang Bang Burger | Forest Rd. | restaurant | 4.0 | 55.0 |
| Costa Coffee | City Point | café | 5.0 | 41.0 |
| Costa Coffee | The Moorgate | takeaway | 5.0 | 0.0 |
| The Queens Head | Denman St. | bar | 5.0 | 187.0 |
Application de recommandation de restaurants
shape: (3, 5)
| business | location | type | rating | capacity |
| --- | --- | --- | --- | --- |
| str | str | str | f64 | f64 |
|------------------|--------------|------------|--------|----------|
| 7burgers | Wakey Wakey | restaurant | 5.0 | 55.0 |
| Bang Bang Burger | Forest Rd. | restaurant | 4.0 | 55.0 |
| Costa Coffee | City Point | café | 5.0 | 41.0 |
- Supprimer les espaces
- Convertir les colonnes rating et capacity
- Créer une colonne d’identifiant unique
Changer le dtype avec une expression
ratings.with_columns(
)
Changer le dtype avec une expression
ratings.with_columns(
pl.col("rating").cast(pl.Int64)
)
shape: (5, 5)
| business | location | type | rating | capacity |
| --- | --- | --- | --- | --- |
| str | str | str | i64 | f64 |
|------------------|--------------|------------|--------|----------|
| 7burgers | Wakey Wakey | restaurant | 5 | 55.0 |
| Bang Bang Burger | Forest Rd. | restaurant | 4 | 55.0 |
| Costa Coffee | City Point | café | 5 | 41.0 |
| Costa Coffee | The Moorgate | takeaway | 5 | 0.0 |
| The Queens Head | Denman St. | bar | 5 | 187.0 |
Changer plusieurs colonnes
ratings.cast( )
Changer plusieurs colonnes
ratings.cast({ })
Changer plusieurs colonnes
ratings.cast({pl.Float64: pl.Int64})
shape: (5, 5)
| business | location | type | rating | capacity |
| --- | --- | --- | --- | --- |
| str | str | str | i64 | i64 |
|------------------|--------------|------------|--------|----------|
| 7burgers | Wakey Wakey | restaurant | 5 | 55 |
| Bang Bang Burger | Forest Rd. | restaurant | 4 | 55 |
| Costa Coffee | City Point | café | 5 | 41 |
| Costa Coffee | The Moorgate | takeaway | 5 | 0 |
| The Queens Head | Denman St. | bar | 5 | 187 |
Nettoyer des données textuelles
shape: (5, 5)
| business | location | type | rating | capacity |
| --- | --- | --- | --- | --- |
| str | str | str | i64 | i64 |
|------------------|-----------------|------------|--------|----------|
| 7burgers | Wakey Wakey | restaurant | 5 | 55 |
| Bang Bang Burger | Forest Rd. | restaurant | 4 | 55 |
| Costa Coffee | City Point | café | 5 | 41 |
| Costa Coffee | The Moorgate | takeaway | 5 | 0 |
| The Queens Head | Denman St. | bar | 5 | 187 |
Nettoyer des données textuelles
.str.contains().str.strip_chars().str.strip_chars_start().str.to_lowercase()- …
Nettoyer des données textuelles
.str.contains().str.strip_chars().str.strip_chars_start().str.to_lowercase()- …
1 https://docs.pola.rs/api/python/stable/reference/expressions/string.html
Nettoyer des données textuelles
.str.contains().str.strip_chars().str.strip_chars_start().str.to_lowercase()- …
1 https://docs.pola.rs/api/python/stable/reference/expressions/string.html
Nettoyer des données textuelles
ratings.with_columns(
)
Nettoyer des données textuelles
ratings.with_columns(
pl.col("business")
)
Nettoyer des données textuelles
ratings.with_columns(
pl.col("business").str.strip_chars_start()
)
shape: (5, 5)
| business | location | type | rating | capacity |
| --- | --- | --- | --- | --- |
| str | str | str | i64 | i64 |
|------------------|--------------|------------|--------|----------|
| 7burgers | Wakey Wakey | restaurant | 5 | 55 |
| Bang Bang Burger | Forest Rd. | restaurant | 4 | 55 |
| Costa Coffee | City Point | café | 5 | 41 |
| Costa Coffee | The Moorgate | takeaway | 5 | 0 |
| The Queens Head | Denman St. | bar | 5 | 187 |
Combiner des données textuelles
shape: (5, 5)
| business | location | type | rating | capacity |
| --- | --- | --- | --- | --- |
| str | str | str | i64 | i64 |
|------------------|-----------------|------------|--------|----------|
| 7burgers | Wakey Wakey | restaurant | 5 | 55 |
| Bang Bang Burger | Forest Rd. | restaurant | 4 | 55 |
| Costa Coffee | City Point | café | 5 | 41 |
| Costa Coffee | The Moorgate | takeaway | 5 | 0 |
| The Queens Head | Denman St. | bar | 5 | 187 |
Combiner des données textuelles
ratings.with_columns(
)
Combiner des données textuelles
ratings.with_columns(
pl.concat_str(
)
Combiner des données textuelles
ratings.with_columns(
pl.concat_str("business", "location"
)
Combiner des données textuelles
ratings.with_columns(
pl.concat_str("business", "location", separator=":")
)
Combiner des données textuelles
ratings.with_columns(
pl.concat_str("business", "location", separator=":").alias("id")
)
shape: (5, 5)
| business | location | type | ... | id |
| --- | --- | --- | --- | --- |
| str | str | str | ... | str |
|------------------|--------------|------------|-----|-------------------------------|
| 7burgers | Wakey Wakey | restaurant | ... | 7burgers:Wakey Wakey |
| Bang Bang Burger | Forest Rd. | restaurant | ... | Bang Bang Burger:Forest Rd. |
| Costa Coffee | City Point | café | ... | Costa Coffee:City Point |
| Costa Coffee | The Moorgate | takeaway | ... | Costa Coffee:The Moorgate |
| The Queens Head | Denman St. | bar | ... | The Queens Head:Denman St. |
Passons à la pratique !
Transformation de données avec Polars
