pandas Getting Started

Category

Scientific Computing & Data Analysis

Provider

pandas

Type

docs

Level

Foundation

Topic

Scientific Computing & Data Analysis

Track

Scientific Computing & Data Analysis

Section

Learning path

Format

Documentation / tutorial

Status

publishable

Commercial

link-only

Featured

no

Fast start

no

Sequence

nan

Priority

A

Primary source

mega_open_hub

Sources

mega_open_hub

ID

0883194eaef97d6d

Pandas documentation

pandas

Core data-cleaning and analysis tool for almost every applied field.

pandas User Guide

pandas

Detailed coverage of indexing, reshaping, joins, missing data, time series, and more.

NumPy: absolute beginners guide

NumPy

Essential for scientific Python, ML preprocessing, simulation, and signal work.

NumPy User Guide

NumPy

Core reference for numerical array work, broadcasting, linear algebra, and scientific workflows.

SciPy documentation

SciPy

Provides optimization, signal processing, integration, stats, and numerics for serious technical work.

Jupyter documentation

Project Jupyter

The default working surface for modern technical learning, experiments, and reproducible reports.

Matplotlib gallery

Matplotlib

You need strong plotting and reporting habits to do research and communicate findings.

GNU Octave

GNU

Useful when you want MATLAB-style workflows without leaving open tooling.

Zephyr Getting Started

Zephyr

Step-by-step setup, build, flash, and run path for Zephyr on Linux and other hosts.

Matomo Getting Started

Matomo

Privacy-conscious analytics platform guide with migration and tracking options.

freeCodeCamp Data Analysis with Python

freeCodeCamp

Practical route into pandas, NumPy, and data analysis projects.

R for Data Science

Hadley Wickham et al.

Excellent second-language path for tidy analysis, EDA, and statistical communication.