Programming & Scientific Computing · Python & Data Science

Python: Data Manipulation and Analysis

Public introduction · full guide in Eikos

Introduction

What this guide covers

Comprehensive mastery of the scientific Python ecosystem: NumPy, Pandas, Matplotlib and Seaborn. From tensor algebra to complete statistical pipelines, with rigorous mathematical foundations, advanced language patterns and expert-level solved exercises.

Overview

Topics covered

  • Introduction
  • The Python Scientific Ecosystem
  • The Fundamental Scientific Stack
  • NumPy
  • Pandas
  • SciPy

Related concepts

Main connections

  • Outliers & influence diagnostics
  • Preprocessing pipelines & transform recipes
  • Analysis of variance (ANOVA)
  • Bootstrap resampling
  • Linear algebra & matrices
  • p-value & significance

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

A∈ℝm×n,strides=(n⋅itemsize,itemsize)
View LaTeX sourceA \in \mathbb{R}^{m \times n}, \quad \text{strides} = (n \cdot \text{itemsize},\ \text{itemsize})