Combining DataFrames

There are two ways DataFrames can be combined depending on the use case: join and concat.

Join

Polars supports all types of join (e.g. left, right, inner, outer). Let's have a closer look on how to join two DataFrames into a single DataFrame. Our two DataFrames both have an 'id'-like column: a and x. We can use those columns to join the DataFrames in this example.

Python Rust

join

df = pl.DataFrame(
    {
        "a": range(8),
        "b": np.random.rand(8),
        "d": [1, 2.0, float("nan"), float("nan"), 0, -5, -42, None],
    }
)

df2 = pl.DataFrame(
    {
        "x": range(8),
        "y": ["A", "A", "A", "B", "B", "C", "X", "X"],
    }
)
joined = df.join(df2, left_on="a", right_on="x")
print(joined)

join

use rand::Rng;
let mut rng = rand::thread_rng();

let df: DataFrame = df!(
    "a" => 0..8,
    "b"=> (0..8).map(|_| rng.gen::<f64>()).collect::<Vec<f64>>(),
    "d"=> [Some(1.0), Some(2.0), None, None, Some(0.0), Some(-5.0), Some(-42.), None]
)
.unwrap();
let df2: DataFrame = df!(
    "x" => 0..8,
    "y"=> &["A", "A", "A", "B", "B", "C", "X", "X"],
)
.unwrap();
let joined = df.join(&df2, ["a"], ["x"], JoinType::Left.into())?;
println!("{}", joined);

shape: (8, 4)
┌─────┬──────────┬───────┬─────┐
│ a   ┆ b        ┆ d     ┆ y   │
│ --- ┆ ---      ┆ ---   ┆ --- │
│ i64 ┆ f64      ┆ f64   ┆ str │
╞═════╪══════════╪═══════╪═════╡
│ 0   ┆ 0.900468 ┆ 1.0   ┆ A   │
│ 1   ┆ 0.965213 ┆ 2.0   ┆ A   │
│ 2   ┆ 0.883848 ┆ NaN   ┆ A   │
│ 3   ┆ 0.623242 ┆ NaN   ┆ B   │
│ 4   ┆ 0.788115 ┆ 0.0   ┆ B   │
│ 5   ┆ 0.185598 ┆ -5.0  ┆ C   │
│ 6   ┆ 0.14701  ┆ -42.0 ┆ X   │
│ 7   ┆ 0.552827 ┆ null  ┆ X   │
└─────┴──────────┴───────┴─────┘

To see more examples with other types of joins, go the User Guide.

Concat

We can also concatenate two DataFrames. Vertical concatenation will make the DataFrame longer. Horizontal concatenation will make the DataFrame wider. Below you can see the result of an horizontal concatenation of our two DataFrames.

Python Rust

hstack

stacked = df.hstack(df2)
print(stacked)

hstack

let stacked = df.hstack(df2.get_columns())?;
println!("{}", stacked);

shape: (8, 5)
┌─────┬──────────┬───────┬─────┬─────┐
│ a   ┆ b        ┆ d     ┆ x   ┆ y   │
│ --- ┆ ---      ┆ ---   ┆ --- ┆ --- │
│ i64 ┆ f64      ┆ f64   ┆ i64 ┆ str │
╞═════╪══════════╪═══════╪═════╪═════╡
│ 0   ┆ 0.900468 ┆ 1.0   ┆ 0   ┆ A   │
│ 1   ┆ 0.965213 ┆ 2.0   ┆ 1   ┆ A   │
│ 2   ┆ 0.883848 ┆ NaN   ┆ 2   ┆ A   │
│ 3   ┆ 0.623242 ┆ NaN   ┆ 3   ┆ B   │
│ 4   ┆ 0.788115 ┆ 0.0   ┆ 4   ┆ B   │
│ 5   ┆ 0.185598 ┆ -5.0  ┆ 5   ┆ C   │
│ 6   ┆ 0.14701  ┆ -42.0 ┆ 6   ┆ X   │
│ 7   ┆ 0.552827 ┆ null  ┆ 7   ┆ X   │
└─────┴──────────┴───────┴─────┴─────┘