docs: Revise and improve 'Concepts' section

crates/polars-lazy/src/frame/mod.rs

@@ -252,7 +252,7 @@ impl LazyFrame {
 
     /// Return a String describing the logical plan.
     ///
-    /// If `optimized` is `true`, explains the optimized plan. If `optimized` is `false,
+    /// If `optimized` is `true`, explains the optimized plan. If `optimized` is `false`,
     /// explains the naive, un-optimized plan.
     pub fn explain(&self, optimized: bool) -> PolarsResult<String> {
         if optimized {

docs/source/_build/API_REFERENCE_LINKS.yml

@@ -26,6 +26,7 @@ python:
   is_duplicated: https://docs.pola.rs/api/python/stable/reference/expressions/api/polars.Expr.is_duplicated.html
   sample: https://docs.pola.rs/api/python/stable/reference/dataframe/api/polars.DataFrame.sample.html
   head: https://docs.pola.rs/api/python/stable/reference/dataframe/api/polars.DataFrame.head.html
+  glimpse: https://docs.pola.rs/api/python/stable/reference/dataframe/api/polars.DataFrame.glimpse.html
   tail: https://docs.pola.rs/api/python/stable/reference/dataframe/api/polars.DataFrame.tail.html
   describe: https://docs.pola.rs/api/python/stable/reference/dataframe/api/polars.DataFrame.describe.html
   col: https://docs.pola.rs/api/python/stable/reference/expressions/col.html

docs/source/src/python/user-guide/concepts/data-types-and-structures.py

@@ -0,0 +1,60 @@
+# --8<-- [start:series]
+import polars as pl
+
+s = pl.Series("ints", [1, 2, 3, 4, 5])
+print(s)
+# --8<-- [end:series]
+
+# --8<-- [start:series-dtype]
+s1 = pl.Series("ints", [1, 2, 3, 4, 5])
+s2 = pl.Series("uints", [1, 2, 3, 4, 5], dtype=pl.UInt64)
+print(s1.dtype, s2.dtype)
+# --8<-- [end:series-dtype]
+
+# --8<-- [start:df]
+from datetime import date
+
+df = pl.DataFrame(
+    {
+        "name": ["Alice Archer", "Ben Brown", "Chloe Cooper", "Daniel Donovan"],
+        "birthdate": [
+            date(1997, 1, 10),
+            date(1985, 2, 15),
+            date(1983, 3, 22),
+            date(1981, 4, 30),
+        ],
+        "weight": [57.9, 72.5, 53.6, 83.1],  # (kg)
+        "height": [1.56, 1.77, 1.65, 1.75],  # (m)
+    }
+)
+
+print(df)
+# --8<-- [end:df]
+
+# --8<-- [start:schema]
+print(df.schema)
+# --8<-- [end:schema]
+
+# --8<-- [start:head]
+print(df.head(3))
+# --8<-- [end:head]
+
+# --8<-- [start:glimpse]
+print(df.glimpse(return_as_string=True))
+# --8<-- [end:glimpse]
+
+# --8<-- [start:tail]
+print(df.tail(3))
+# --8<-- [end:tail]
+
+# --8<-- [start:sample]
+import random
+
+random.seed(42)  # For reproducibility.
+
+print(df.sample(2))
+# --8<-- [end:sample]
+
+# --8<-- [start:describe]
+print(df.describe())
+# --8<-- [end:describe]

docs/source/src/python/user-guide/concepts/expressions.py

@@ -1,16 +1,105 @@
+# --8<-- [start:expression]
 import polars as pl
 
+pl.col("weight") / (pl.col("height") ** 2)
+# --8<-- [end:expression]
+
+# --8<-- [start:print-expr]
+bmi_expr = pl.col("weight") / (pl.col("height") ** 2)
+print(bmi_expr)
+# --8<-- [end:print-expr]
+
+# --8<-- [start:df]
+from datetime import date
+
 df = pl.DataFrame(
     {
-        "foo": [1, 2, 3, None, 5],
-        "bar": [1.5, 0.9, 2.0, 0.0, None],
+        "name": ["Alice Archer", "Ben Brown", "Chloe Cooper", "Daniel Donovan"],
+        "birthdate": [
+            date(1997, 1, 10),
+            date(1985, 2, 15),
+            date(1983, 3, 22),
+            date(1981, 4, 30),
+        ],
+        "weight": [57.9, 72.5, 53.6, 83.1],  # (kg)
+        "height": [1.56, 1.77, 1.65, 1.75],  # (m)
     }
 )
 
-# --8<-- [start:example1]
-pl.col("foo").sort().head(2)
-# --8<-- [end:example1]
+print(df)
+# --8<-- [end:df]
+
+# --8<-- [start:select-1]
+result = df.select(
+    bmi=bmi_expr,
+    avg_bmi=bmi_expr.mean(),
+    ideal_max_bmi=25,
+)
+print(result)
+# --8<-- [end:select-1]
+
+# --8<-- [start:select-2]
+result = df.select(deviation=(bmi_expr - bmi_expr.mean()) / bmi_expr.std())
+print(result)
+# --8<-- [end:select-2]
+
+# --8<-- [start:with_columns-1]
+result = df.with_columns(
+    bmi=bmi_expr,
+    avg_bmi=bmi_expr.mean(),
+    ideal_max_bmi=25,
+)
+print(result)
+# --8<-- [end:with_columns-1]
+
+# --8<-- [start:filter-1]
+result = df.filter(
+    pl.col("birthdate").is_between(date(1982, 12, 31), date(1996, 1, 1)),
+    pl.col("height") > 1.7,
+)
+print(result)
+# --8<-- [end:filter-1]
+
+# --8<-- [start:group_by-1]
+result = df.group_by(
+    (pl.col("birthdate").dt.year() // 10 * 10).alias("decade"),
+).agg(pl.col("name"))
+print(result)
+# --8<-- [end:group_by-1]
+
+# --8<-- [start:group_by-2]
+result = df.group_by(
+    (pl.col("birthdate").dt.year() // 10 * 10).alias("decade"),
+    (pl.col("height") < 1.7).alias("short?"),
+).agg(pl.col("name"))
+print(result)
+# --8<-- [end:group_by-2]
+
+# --8<-- [start:group_by-3]
+result = df.group_by(
+    (pl.col("birthdate").dt.year() // 10 * 10).alias("decade"),
+    (pl.col("height") < 1.7).alias("short?"),
+).agg(
+    pl.len(),
+    pl.col("height").max().alias("tallest"),
+    pl.col("weight", "height").mean().name.prefix("avg_"),
+)
+print(result)
+# --8<-- [end:group_by-3]
 
-# --8<-- [start:example2]
-df.select(pl.col("foo").sort().head(2), pl.col("bar").filter(pl.col("foo") == 1).sum())
-# --8<-- [end:example2]
+# --8<-- [start:expression-expansion-1]
+expr = (pl.col(pl.Float64) * 1.1).name.suffix("*1.1")
+result = df.select(expr)
+print(result)
+# --8<-- [end:expression-expansion-1]
+
+# --8<-- [start:expression-expansion-2]
+df2 = pl.DataFrame(
+    {
+        "ints": [1, 2, 3, 4],
+        "letters": ["A", "B", "C", "D"],
+    }
+)
+result = df2.select(expr)
+print(result)
+# --8<-- [end:expression-expansion-2]

docs/source/src/python/user-guide/concepts/lazy-vs-eager.py

@@ -1,5 +1,8 @@
+# --8<-- [start:import]
 import polars as pl
 
+# --8<-- [end:import]
+
 # --8<-- [start:eager]
 
 df = pl.read_csv("docs/assets/data/iris.csv")
@@ -18,3 +21,25 @@
 
 df = q.collect()
 # --8<-- [end:lazy]
+
+# --8<-- [start:explain]
+print(q.explain())
+# --8<-- [end:explain]
+
+# --8<-- [start:explain-expression-expansion]
+schema = pl.Schema(
+    {
+        "int_1": pl.Int16,
+        "int_2": pl.Int32,
+        "float_1": pl.Float64,
+        "float_2": pl.Float64,
+        "float_3": pl.Float64,
+    }
+)
+
+print(
+    pl.LazyFrame(schema=schema)
+    .select((pl.col(pl.Float64) * 1.1).name.suffix("*1.1"))
+    .explain()
+)
+# --8<-- [end:explain-expression-expansion]

docs/source/src/rust/Cargo.toml

@@ -31,8 +31,8 @@ path = "user-guide/getting-started.rs"
 required-features = ["polars/lazy", "polars/temporal", "polars/round_series", "polars/strings"]
 
 [[bin]]
-name = "user-guide-concepts-data-structures"
-path = "user-guide/concepts/data-structures.rs"
+name = "user-guide-concepts-data-types-and-structures"
+path = "user-guide/concepts/data-types-and-structures.rs"
 
 [[bin]]
 name = "user-guide-concepts-contexts"
@@ -41,7 +41,7 @@ required-features = ["polars/lazy"]
 [[bin]]
 name = "user-guide-concepts-expressions"
 path = "user-guide/concepts/expressions.rs"
-required-features = ["polars/lazy"]
+required-features = ["polars/lazy", "polars/temporal", "polars/is_between"]
 [[bin]]
 name = "user-guide-concepts-lazy-vs-eager"
 path = "user-guide/concepts/lazy-vs-eager.rs"