All Projects → briatte → Ida

briatte / Ida

Introduction to Data Analysis, using R (2013)

Programming Languages

r
7636 projects

Projects that are alternatives of or similar to Ida

dsr
Introduction to Data Science with R (2017)
Stars: ✭ 25 (-86.11%)
Mutual labels:  course, data-analysis
R
Exercises (incl. analyses) with R language (math+statistics)
Stars: ✭ 462 (+156.67%)
Mutual labels:  data-analysis, course
Dat8
General Assembly's 2015 Data Science course in Washington, DC
Stars: ✭ 1,516 (+742.22%)
Mutual labels:  data-analysis, course
Visualize ml
Python package for consolidated and extensive Univariate,Bivariate Data Analysis and Visualization catering to both categorical and continuous datasets.
Stars: ✭ 160 (-11.11%)
Mutual labels:  data-analysis
Teachingmaterial
Various teaching material
Stars: ✭ 159 (-11.67%)
Mutual labels:  data-analysis
Matplotplusplus
Matplot++: A C++ Graphics Library for Data Visualization 📊🗾
Stars: ✭ 2,433 (+1251.67%)
Mutual labels:  data-analysis
Matplotlib Doc Zh
📖 [译] Matplotlib 用户指南
Stars: ✭ 178 (-1.11%)
Mutual labels:  data-analysis
Etl unicorn
数据可视化, 数据挖掘, 数据处理 ETL
Stars: ✭ 156 (-13.33%)
Mutual labels:  data-analysis
Python practice of data analysis and mining
《Python数据分析与挖掘实战》随书源码与数据
Stars: ✭ 172 (-4.44%)
Mutual labels:  data-analysis
Dabestr
Data Analysis with Bootstrap Estimation in R
Stars: ✭ 169 (-6.11%)
Mutual labels:  data-analysis
Pipeline
the `pipeline` shell command
Stars: ✭ 168 (-6.67%)
Mutual labels:  data-analysis
Report Designer
🚀 打印设计、可视化、大屏、编辑器、设计器、数据分析、报表设计、组件化、表单设计、h5页面、调查问卷、pdf生成、流程图、试卷、SVG、图形元素、物联网
Stars: ✭ 160 (-11.11%)
Mutual labels:  data-analysis
Covid19 Severity Prediction
Extensive and accessible COVID-19 data + forecasting for counties and hospitals. 📈
Stars: ✭ 170 (-5.56%)
Mutual labels:  data-analysis
Dslsofmath
Domain Specific Languages of Mathematics
Stars: ✭ 159 (-11.67%)
Mutual labels:  course
Lunatech Scala 2 To Scala3 Course
Lunatech course - "Moving forward from Scala 2 to Scala 3"
Stars: ✭ 174 (-3.33%)
Mutual labels:  course
Cyberchef
The Cyber Swiss Army Knife - a web app for encryption, encoding, compression and data analysis
Stars: ✭ 13,674 (+7496.67%)
Mutual labels:  data-analysis
Eegrunt
A Collection Python EEG (+ ECG) Analysis Utilities for OpenBCI and Muse
Stars: ✭ 171 (-5%)
Mutual labels:  data-analysis
Countly Sdk Web
Countly Product Analytics SDK for websites and web applications
Stars: ✭ 165 (-8.33%)
Mutual labels:  data-analysis
Pandas Datareader
Extract data from a wide range of Internet sources into a pandas DataFrame.
Stars: ✭ 2,183 (+1112.78%)
Mutual labels:  data-analysis
Airbyte
Airbyte is an open-source EL(T) platform that helps you replicate your data in your warehouses, lakes and databases.
Stars: ✭ 4,919 (+2632.78%)
Mutual labels:  data-analysis

README

Ivaylo Petev and myself use this repository to teach an undergraduate introduction to data analysis. The course is online.

If you are reading the course on its online pages, just replace the .html extension of a page by .R to download the underlying code.

HOWTO

The course pages are formatted in R Markdown syntax and were converted to HTML with knitr 1.4:

install.packages("knitr")
citation("knitr")

The knitting routine is in the .Rprofile. To compile the whole course, set the IDA folder as your working directory and then type ida.build() (takes a bit more than five minutes on optic fiber).

Other files are called from the code/ and data/ folders. Most datasets are downloaded on the fly if they are missing from the data/ folder, so make sure that you are online while running the scripts.

The whole course was coded and taught with RStudio. The code was ran on R 2.15.2, 2.15.3, 3.0.0 and 3.0.1, on a MacBook Air running OS X 10.8 and Mac OS X 10.9. Most plots use ggplot2 version 0.9.3.1 (just in case compatibility breaks at some point).

CREDITS

Thanks to the Sciences Po Reims staff, who offered invaluable support, and to the small group of students who enrolled in (and survived to) the course. The R-2013-Lyon slides have a bit more detail on the practicals.

Bits and pieces of the code were posted to Gist, RPubs and Stack Overflow during development. Thanks to the great R developer and user communities that live online, and which we are now proud to count ourselves in.

If you share the spirit of all this, you should consider joining the Foundation for Open Access Statistics and check out places like OpenCPU, the Open Knowledge Foundation and other initiatives in open access, open data, open source and open science.

HISTORY

Aug 2013: better data management, with large or multiple-file datasets read from ZIP archives. Switched datasets to .csv thanks to GitHub.

Jul 2013: typos and broken links. Removed some functions in .Rprofile that are now part of the questionr package.

Jun-2013: first draft. Everything kind of works, Sessions 5--7 are unlisted, the code/ folder contains a few more exercises. That's it for now!

May-2013: added more course content and better resolution (100dpi) for all plots.

Apr-2013: added a lot of course content and cleaner plots. Also adding the R-2013-Lyon folder for a conference presentation on the course.

Mar-2013: reviewed course structure: less files, more code, tons of new examples and exercises.

Feb-2013: more efficient .Rprofile functions and improved knitr routine, tidier code on the early sessions.

Jan-2013: first release.

First release: January 2013.
Last revised: August 2013.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].