R for Data Science

Category

Scientific Computing & Data Analysis

Provider

Hadley Wickham et al.

Type

resource

Level

Build

Topic

Scientific Computing & Data Analysis

Track

Scientific Computing & Data Analysis

Section

Learning path

Format

Book

Status

publishable

Commercial

link-only

Featured

yes

Fast start

no

Sequence

6.0

Priority

Standard

Primary source

direct_links_master

Sources

direct_links_master, mega_open_hub

ID

e55d734ea8713528

SciPy documentation

SciPy

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

freeCodeCamp Data Analysis with Python

freeCodeCamp

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

Matplotlib gallery

Matplotlib

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

pandas User Guide

pandas

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

NumPy User Guide

NumPy

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

Neuromatch Neural Data Science

Neuromatch Academy

Excellent bridge into modern computational neuroscience and data handling.

Pandas documentation

pandas

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

NumPy: absolute beginners guide

NumPy

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

Jupyter documentation

Project Jupyter

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

pandas Getting Started

pandas

Practical route into tabular wrangling, series/dataframes, and common analysis patterns.

GNU Octave

GNU

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

NCBI Genome Data

NCBI

Core data source for sequence retrieval, metadata, and organism-level browsing.