brassfibre
Provides multiple-dtype columner storage, known as DataFrame in pandas/R.
Series
Single-dtype 1-dimentional vector with label (index).
Creation
extern crate brassfibre;
use brassfibre::prelude::*;
let values: Vec<i64> = vec![1, 2, 3, 4, 3];
let index: Vec<i64> = vec![10, 20, 30, 40, 50];
let s = Series::<i64, i64>::new(values, index);
println!("{:?}", &s);
// 10 1
// 20 2
// 30 3
// 40 4
// 50 3
Selection
println!("{:?}", &s.locs(&vec![10, 40, 50]));
// 10 1
// 40 4
// 50 3
println!("{:?}", &s.ilocs(&vec![2, 3, 4]));
// 30 3
// 40 4
// 50 3
Calculation
println!("{:?}", &(&b + 5));
// 10 2
// 20 3
// 30 4
// 40 5
// 50 4
println!("{:?}", &s.sum());
// 13
println!("{:?}", &s.describe());
// count 5
// mean 2.6
// std 1.019803902718557
// min 1
// max 4
println!("{:?}", s.value_counts());
// 3 2
// 2 1
// 1 1
// 4 1
Group By
let sg = s.groupby(vec![1, 1, 1, 2, 2]);
println!("{:?}", sg.get_group(&1));
// 10 1
// 20 2
// 30 3
println!("{:?}", sg.sum());
// 1 6
// 2 7
DataFrame
Multiple-dtype 2-dimentional vector with labels (index and columns).
Creation
#[macro_use]
extern crate brassfibre;
use brassfibre::prelude::*;
let values = vec![array![1, 2, 3, 4, 5],
array![6.1, 7.1, 8.1, 9.1, 10.1],
array![11, 12, 13, 14, 15]];
let df = DataFrame::from_vec(values,
vec![10, 20, 30, 40, 50],
vec!["X", "YYY", "ZZ"]);
println!("{:?}", &df);
// X YYY ZZ
// 10 1 6.1 11
// 20 2 7.1 12
// 30 3 8.1 13
// 40 4 9.1 14
// 50 5 10.1 15
Selection
by multiple index labels
println!("{:?}", &df.locs(&vec![20, 30, 40]));
// X YYY ZZ
// 20 2 7.1 12
// 30 3 8.1 13
// 40 4 9.1 14
by multiple index locations
println!("{:?}", &df.ilocs(&vec![0, 2, 1]));
// X YYY ZZ
// 10 1 6.1 11
// 30 3 8.1 13
// 20 2 7.1 12
Group By
get group
let dg = df.groupby(vec!["A", "A", "B", "A", "B"]);
println!("{:?}", &dg.get_group(&"A"));
// X YYY ZZ
// 10 1 6.1 11
// 20 2 7.1 12
// 40 4 9.1 14
Reshaping
inner join
let values2 = vec![array![1.1, 2.1, 3.1],
array![6, 7, 8]];
let df2 = DataFrame::from_vec(values2,
vec![20, 30, 40],
vec!["X2", "Y2"]);
let j = df.join_inner(&df2);
println!("{:?}", &j);
// X YYY ZZ X2 Y2
// 20 2 7.1 12 1.1 6
// 30 3 8.1 13 2.1 7
// 40 4 9.1 14 3.1 8
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