Reputation: 1410
I want to read in data into polars
dataframe from mysql
database. I am using sqlx
.
sqlx
generates a vector of Structs for example: Vec<Country>
below:
From sqlx
Docs:
// no traits are needed
struct Country { country: String, count: i64 }
let countries = sqlx::query_as!(Country,
"
SELECT country, COUNT(*) as count
FROM users
GROUP BY country
WHERE organization = ?
",
organization
)
.fetch_all(&pool) // -> Vec<Country>
.await?;
// countries[0].country
// countries[0].count
How do i use this Vec<Country>
to generate a polars dataframe
From polars
Docs:
use polars_core::prelude::*;
let s0 = Series::new("a", &[1i64, 2, 3]);
let s1 = Series::new("b", &[1i64, 1, 1]);
let s2 = Series::new("c", &[2i64, 2, 2]);
let list = Series::new("foo", &[s0, s1, s2]);
let s0 = Series::new("B", [1, 2, 3]);
let s1 = Series::new("C", [1, 1, 1]);
let df = DataFrame::new(vec![list, s0, s1]).unwrap();
The only solution i can think of is, if i can create a series for every column/Data inside the Country
struct and use those individual series to create a dataframe.
I have no idea how to break down a Vec<Country>
into Vec<country>
and Vec<count>
Upvotes: 3
Views: 3527
Reputation: 14660
You could use the builders for that or collect from iterators. Collecting from iterators is often fast, but in this case it requires you to loop the Vec<Country>
twice, so you should benchmark.
Below is an example function for both the solutions shown.
use polars::prelude::*;
struct Country {
country: String,
count: i64,
}
fn example_1(values: &[Country]) -> (Series, Series) {
let ca_country: Utf8Chunked = values.iter().map(|v| &*v.country).collect();
let ca_count: NoNull<Int64Chunked> = values.iter().map(|v| v.count).collect();
let mut s_country: Series = ca_country.into();
let mut s_count: Series = ca_count.into_inner().into();
s_country.rename("country");
s_count.rename("country");
(s_count, s_country)
}
fn example_2(values: &[Country]) -> (Series, Series) {
let mut country_builder = Utf8ChunkedBuilder::new("country", values.len(), values.len() * 5);
let mut count_builder = PrimitiveChunkedBuilder::<Int64Type>::new("count", values.len());
values.iter().for_each(|v| {
country_builder.append_value(&v.country);
count_builder.append_value(v.count)
});
(
count_builder.finish().into(),
country_builder.finish().into(),
)
}
Btw, if you want maximum performance, I really recommend connector-x. It has got polars and arrow integration and has got insane performance.
Upvotes: 5
Reputation: 2243
I do not know about the structure of these DataFrame
s or Series
but if you want to split out a vector of structs, you can write a small reducer that iterates over the vector's contents and pushes them into multiple new vectors.
A simplified playground snippet: https://play.rust-lang.org/?version=stable&mode=debug&edition=2018&gist=f698866751214fc3f44c348b7c4f80c5
struct A(u8, i8);
fn main() {
let v = vec![A(1, 4), A(2, 6), A(3, 5)];
let result = v.into_iter()
.fold((vec![], vec![]), |(mut u, mut i), item| {
u.push(item.0);
i.push(item.1);
(u, i)
});
dbg!(result);
// `result` is just a tuple of vectors
// let (unsigneds, signeds): (Vec<u8>, Vec<i8>) = result;
}
You basically take a vector of structs, you iterate over them and fold them into the provided new (empty) vectors one by one. At the end, the result is returned (a tuple of 2 vectors). You can do what you want with these now.
Upvotes: 2