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Sub-skill of polars: 3. Expression API.
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| name | polars-3-expression-api |
| description | Sub-skill of polars: 3. Expression API. |
| version | 1.0.0 |
| category | data-analysis |
| type | reference |
| scripts_exempt | true |
Basic Expressions:
import polars as pl
df = pl.DataFrame({
"a": [1, 2, 3, 4, 5],
"b": [10, 20, 30, 40, 50],
"c": ["x", "y", "x", "y", "x"],
"d": [1.5, 2.5, 3.5, 4.5, 5.5]
})
# Column selection
df.select(pl.col("a"))
df.select(pl.col("a", "b", "c"))
df.select(pl.col("^a.*$")) # Regex pattern
df.select(pl.all())
df.select(pl.exclude("c"))
# Arithmetic operations
df.select([
pl.col("a"),
(pl.col("a") + pl.col("b")).alias("sum"),
(pl.col("a") * pl.col("d")).alias("product"),
(pl.col("b") / pl.col("a")).alias("ratio"),
(pl.col("a") ** 2).alias("squared"),
(pl.col("a") % 2).alias("modulo")
])
# Conditional expressions
df.select([
pl.col("a"),
pl.when(pl.col("a") > 3)
.then(pl.lit("high"))
.otherwise(pl.lit("low"))
.alias("category"),
pl.when(pl.col("a") < 2)
.then(pl.lit("low"))
.when(pl.col("a") < 4)
.then(pl.lit("medium"))
.otherwise(pl.lit("high"))
.alias("tier")
])
# String operations
df_str = pl.DataFrame({
"text": ["Hello World", "Polars is Fast", "Data Analysis"]
})
df_str.select([
pl.col("text"),
pl.col("text").str.to_lowercase().alias("lower"),
pl.col("text").str.to_uppercase().alias("upper"),
pl.col("text").str.len_chars().alias("length"),
pl.col("text").str.split(" ").alias("words"),
pl.col("text").str.contains("a").alias("has_a"),
pl.col("text").str.replace("a", "X").alias("replaced")
])
Advanced Expressions:
# List operations
df_list = pl.DataFrame({
"values": [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
})
df_list.select([
pl.col("values"),
pl.col("values").list.len().alias("count"),
pl.col("values").list.sum().alias("sum"),
pl.col("values").list.mean().alias("mean"),
pl.col("values").list.first().alias("first"),
pl.col("values").list.last().alias("last"),
pl.col("values").list.get(0).alias("index_0"),
pl.col("values").list.contains(5).alias("has_5")
])
# Struct operations
df_struct = pl.DataFrame({
"point": [{"x": 1, "y": 2}, {"x": 3, "y": 4}]
})
df_struct.select([
pl.col("point"),
pl.col("point").struct.field("x").alias("x"),
pl.col("point").struct.field().alias()
])
df_dt = pl.DataFrame({
: pl.date_range(
datetime(, , ),
datetime(, , ),
,
eager=
)
})
df_dt.select([
pl.col(),
pl.col().dt.year().alias(),
pl.col().dt.month().alias(),
pl.col().dt.day().alias(),
pl.col().dt.weekday().alias(),
pl.col().dt.week().alias(),
pl.col().dt.quarter().alias(),
pl.col().dt.strftime().alias()
])