The Functional Approach to Data Processing

One of the strengths of the DataFrame library is its functional programming approach to data processing.
This approach offers several benefits:

Immutability: Operations create new Series without modifying the original data
Composability: Operations can be easily combined into complex workflows
Readability: The intent of the code is clear and follows a declarative style
Maintainability: Logic is broken down into smaller, reusable functions

DataFrame Library API Reference

Core Components

Serie

A column of data with elements of the same type, providing the fundamental building block of the library.

Dataframe

A collection of named Series that can have different element types.

Element Processing

filter

Creates a new Serie containing only elements that satisfy a predicate function.

find

Finds the first element that matches a predicate function.

forEach

Iterates over each element in a Serie to perform an operation without changing the Serie.

map

Transforms each element in a Serie using a callback function, returning a new Serie.

parallel_map

Transforms elements in parallel using multiple threads for better performance.

print

Outputs Serie contents to the console for debugging and inspection.

reduce

Reduces a Serie to a single value by applying a function against an accumulator.

reject

Creates a new Serie excluding elements that satisfy a predicate function.

where

Alternative to filter for selecting elements that match specified criteria.

Control Flow

compose

Creates a new function by composing multiple functions together.

if_then_else

Conditionally transforms elements based on a predicate with true/false paths.

map_if

Conditionally applies a transformation to elements that match a condition.

memoise

Caches function results to avoid redundant computation on repeated calls.

pipe

Composes multiple operations into a reusable processing pipeline.

switch

Selects from multiple transformations based on element values.

whenAll

Executes a function when all conditions are satisfied.

Series Creation

for

Creates a Serie by applying a function to each index in a range.

ones

Creates a Serie filled with ones of a specified length.

range

Creates a Serie with a sequence of numbers in a specified range.

zeros

Creates a Serie filled with zeros of a specified length.

Series Manipulation

chain

Combines multiple Series sequentially into a single Serie.

concat

Concatenates multiple Series into a single Serie.

chunk

Splits a Serie into chunks of a specified size.

flatMap

function applies a transformation to each element in a Serie, where the transformation returns a Serie for each element, and then flattens all those Series into a single Serie. It's essentially a combination of map followed by a flatten operation.

flatten

Converts a Serie of arrays or nested Series into a flat Serie.

merge

Combines multiple Series with a custom merge function.

partition

Divides a Serie into two Series based on a predicate function.

skip

Creates a Serie that skips the first n elements from the source Serie.

slice

Creates a Serie from a subset of elements specified by start and end indices.

split

Divides a Serie into multiple equal-sized parts.

take

Creates a Serie with the first n elements from the source Serie.

unzip

Separates a Serie of tuples into multiple Series.

zip

Combines elements from multiple Series into tuples based on position.

Ordering & Grouping

sort

Creates a sorted copy of a Serie in ascending or descending order.

orderBy

Sorts a Serie based on a key function that determines the sorting order.

groupBy

Groups Serie elements by a key function and returns a map of keys to Series.

unique

Creates a Serie with duplicate elements removed.

Formatting

format

Converts a Serie to a formatted string representation with customizable options.

IO

CSV

Read and write CSV files with configurable delimiters, quoting, headers, and automatic type detection.

JSON

Read and write JSON files as arrays of objects, with automatic type mapping and pretty-printing support.

Binary

Platform-independent binary serialization with endianness handling, type safety, and custom type registration.

Maching learning

RandomForest

Maching Learning

The RandomForest class provides an implementation of the Random Forest algorithm integrated with the DataFrame library.

Lime

Maching Learning

LIME (Local Interpretable Model-agnostic Explanations) is a technique designed to explain the predictions of any machine learning model by approximating it locally with an interpretable model.

Genetic Algorithm

Maching Learning

Evolutionary optimization using selection, crossover, and mutation operators for both numerical and combinatorial problems.

Bee Algorithm

Maching Learning

Artificial Bee Colony (ABC) optimization inspired by honey bee foraging behavior for continuous and discrete problems.

Algebra

Linear Algebra

Matrix and vector operations including determinant, inverse, eigenvalues, cross/dot product, transpose, and linear solve.

Algorithmic

Algorithmic Functions

Harmonic diffusion solver using Laplacian smoothing on meshes with fixed boundary conditions.

Attribute Decomposition

Manager

Manage attribute decomposition workflows on Series.

Decomposer

Base interface for attribute decomposition strategies.

Coordinates

Decompose vector attributes into coordinate components.

Components

Decompose matrix/tensor attributes into individual components.

Geometry

Geometry Functions

Geometric computations including area, normals, curvature, distance fields, lengths, and sphere generation.

Geophysics

Geophysics Functions

InSAR line-of-sight projection, fringe generation, and displacement field analysis for remote sensing.

Interpolation

Interpolation Methods

IDW, RBF, Nearest Neighbor, and Natural Neighbor interpolation for scattered 2D/3D point data.

Kriging

Ordinary Kriging with variogram models (Spherical, Exponential, Gaussian, Matérn) for geostatistical interpolation.

Grid Generation

Create 2D/3D Cartesian grids from dimensions or point sets, with RBF-based grid interpolation.

Mathematics

Mathematical Functions

Arithmetic, normalization, bounds, random generation, weighted sums, and NaN handling utilities.

Meshing

Mesh

2D/3D mesh class with topology computation, attribute management, border detection, and contour extraction.

Statistics

Statistics

Descriptive statistics including mean, variance, covariance, correlation, quantiles, and more.

Bins / Histograms

Binning functions to create histograms with automatic or custom ranges.