Indexing a Series

Slice Indexing with series.slice(idx, len)

The returned Series is a view of self and does not copy the data. If _offset is negative, it counts from the end of the array.

Function declaration: fn slice(&self, _offset: i64, _length: usize) -> Series

Example:

#![allow(unused)]
fn main() {
let s = Series::new("field_name", [0i32, 1, 8]);
let s2 = s.slice(2, 4);
}

Indexing by Position

series.take_slice(&[u32])

Use take_slice when the index array is stored in a slice.

#![allow(unused)]
fn main() {
let s = Series::new("foo".into(), [1i32, 2, 4, 5, 7, 3]);
let s2 = s.take_slice(&[1, 3, 5]);
// s2 == Series[2, 5, 3]
}

series.take(&IdxCa)

Use the take method when indices are stored in the IdxCa type. IdxCa is an alias for ChunkedArray<UInt32Type>.

#![allow(unused)]
fn main() {
let s = Series::new("foo".into(), [1i32, 2, 4, 5, 7, 3]);
let idx0: IdxCa = IdxCa::from_vec("index".into(), vec![1, 3, 4]);
let res0 = s.take(&idx0).unwrap();
println!("{}", res0);
}

Logical Indexing

series.filter(bool_idxs) bool_idx is a logical index, essentially an array of boolean values. Elements corresponding to true in bool_idx are copied from the series and returned. The implicit requirement is that len(bool_idx) == len(series). bool_idx is of type BooleanChunked, an alias for ChunkedArray. The series defines boolean operation functions, supporting comparisons between a Series and a single value, as well as between two Series.

#![allow(unused)]
fn main() {
let s1 = Series::new("field_name1", vec![0i32, 1, 2, 5, 8]);
let s2 = Series::new("field_name2", vec![2i32, -1, 3, -5, 8]);
let idx = s1.gt(&s2).unwrap() & s1.lt_eq(5).unwrap();
let s2 = s1.filter(&idx).unwrap();
}

Logical Operations

In series.filter(bool_idxs), bool_idxs is of type BooleanChunked, which can be returned by logical operations.

The *_missing series of functions are used to compare two Series or ChunkedArray for equality, taking into account possible missing values (i.e., None or NaN). In many cases, directly comparing two Series or ChunkedArray containing missing values may yield inaccurate results because None or NaN is not equal to any value, including themselves. The equal_missing function provides a way to handle this situation by treating elements with missing values at the same position as equal.