How to merge two DataFrames with different columns / sizes - dataframe

Question

Looking for a way to combine two DataFrames.
df1:
shape: (2, 2)
┌────────┬──────────────────────┐
│ Fruit ┆ Phosphorus (mg/100g) │
│ --- ┆ --- │
│ str ┆ i32 │
╞════════╪══════════════════════╡
│ Apple ┆ 11 │
├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ Banana ┆ 22 │
└────────┴──────────────────────┘
df2:
shape: (1, 3)
┌──────┬─────────────────────┬──────────────────────┐
│ Name ┆ Potassium (mg/100g) ┆ Phosphorus (mg/100g) │
│ --- ┆ --- ┆ --- │
│ str ┆ i32 ┆ i32 │
╞══════╪═════════════════════╪══════════════════════╡
│ Pear ┆ 115 ┆ 12 │
└──────┴─────────────────────┴──────────────────────┘
Result should be:
shape: (3, 3)
+--------+----------------------+---------------------+
| Fruit | Phosphorus (mg/100g) | Potassium (mg/100g) |
| --- | --- | --- |
| str | i32 | i32 |
+========+======================+=====================+
| Apple | 11 | null |
+--------+----------------------+---------------------+
| Banana | 22 | null |
+--------+----------------------+---------------------+
| Pear | 12 | 115 |
+--------+----------------------+---------------------+
Here is the code sniplet I try to make work:
use polars::prelude::*;
fn main() {
let df1: DataFrame = df!("Fruit" => &["Apple", "Banana"],
"Phosphorus (mg/100g)" => &[11, 22])
.unwrap();
let df2: DataFrame = df!("Name" => &["Pear"],
"Potassium (mg/100g)" => &[115],
"Phosphorus (mg/100g)" => &[12]
)
.unwrap();
let df3: DataFrame = df1
.join(&df2, ["Fruit"], ["Name"], JoinType::Left, None)
.unwrap();
assert_eq!(df3.shape(), (3, 3));
println!("{}", df3);
}
It's a FULL OUTER JOIN I am looking for ...
The ERROR I get:
thread 'main' panicked at 'assertion failed: (left == right)
left: (2, 4),
right: (3, 3)', src\main.rs:18:5

Answer 1

You need to explicitly specify the columns you are going to merge, and use JoinType::Outer for the outer join:
use polars::prelude::*;
fn main() {
let df1: DataFrame = df!("Fruit" => &["Apple", "Banana"],
"Phosphorus (mg/100g)" => &[11, 22])
.unwrap();
let df2: DataFrame = df!("Name" => &["Pear"],
"Potassium (mg/100g)" => &[115],
"Phosphorus (mg/100g)" => &[12]
)
.unwrap();
let df3: DataFrame = df1
.join(
&df2,
["Fruit", "Phosphorus (mg/100g)"],
["Name", "Phosphorus (mg/100g)"],
JoinType::Outer,
None).unwrap();
assert_eq!(df3.shape(), (3, 3));
println!("{}", df3);
}

Answer 2

Thanks to #Ayaz :) I was able to make a generic version, one where I do not need to specify the shared column names each time.
Here is my version of the FULL OUTER JOIN of two DataFrames:
use polars::prelude::*;
use array_tool::vec::{Intersect};
fn concat_df(df1: &DataFrame, df2: &DataFrame) -> Result<DataFrame, PolarsError> {
if df1.is_empty() {
return Ok(df2.clone());
}
let df1_column_names = df1.get_column_names();
let df2_column_names = df2.get_column_names();
let common_column_names = &df1_column_names.intersect(df2_column_names)[..];
df1.join(
df2,
common_column_names,
common_column_names,
JoinType::Outer,
None,
)
}