Supposing I have a vector of structs like so:
struct Test {
id:u32,
amount:u32
}
fn main() {
let test_vec:Vec<Test> = vec![Test{id:1,amount:3}, Test{id:3,amount:4}];
}
Is there a way to get this into a polars dataframe with the column names being the struct fields?
Hoping to get an output as follows:
id amount
0 1 3
1 3 4
I dislike the accepted answer for a couple of reasons
chrono::NaiveDate field - it will come back as a str in your DataFrame.I think a much better solution is a macro:
macro_rules! struct_to_dataframe {
($input:expr, [$($field:ident),+]) => {
{
let len = $input.len().to_owned();
// Extract the field values into separate vectors
$(let mut $field = Vec::with_capacity(len);)*
for e in $input.into_iter() {
$($field.push(e.$field);)*
}
df! {
$(stringify!($field) => $field,)*
}
}
};
}
You should be able to call it like so:
struct Test {
id:u32,
amount:u32
}
impl Test {
fn new(id:u32, amount:u32) -> Self{
Test{id,amount}
}
}
let test_vec:Vec<Test> = vec![Test::new(1,3), Test::new(3,4)];
let df = struct_to_dataframe!(test_vec, [id, amount]).unwrap();
with_capacity(), for much more efficient creation of struct vectors with many elements.After a lot of head banging, I found the following solution.
If you have a vector of a custom struct, to get it into a Polars dataframe you can do the following:
// 1. Derive serde::Serialize for your struct
#[derive(Serialize)]
struct Test {
id:u32,
amount:u32
}
// (Adding new method here for quality of life).
impl Test {
fn new(id:u32, amount:u32) -> Self{
Test{id,amount}
}
}
// 2. Jsonify your struct Vec
let test_vec:Vec<Test> = vec![Test::new(1,3), Test::new(3,4)];
let json = serde_json::to_string(&test_vec).unwrap();
// 3. Create cursor from json
let cursor = Cursor::new(json);
// 4. Create polars DataFrame from reading cursor as json
let df = JsonReader::new(cursor)
.finish()
.unwrap();