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https://github.com/infoculture/awesome-datajournalism

Awesome list for data journalists and future data journalists
https://github.com/infoculture/awesome-datajournalism

List: awesome-datajournalism

awesome awesome-list data-driven-journalism data-journalism data-journalists data-visualization journalists opendata visualization

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Awesome list for data journalists and future data journalists

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README 

        
# Awesome Data Journalism [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)



*An open source, open data and just open Data Journalism repository to learn and understand practical data journalism.*



### Table of contents



* [What is Data Journalism?](#what-is-data-journalism)

* [Handbooks and books](#handbooks-and-books)

* [Formal education](#formal-education)

* [MOOC's](#moocs)

* [Data Sets ](#data-sets)

* [Web scraping](#web-scraping)

* [Facebook Accounts](#facebook-accounts)

* [Twitter Accounts ](#twitter-accounts )

* [Visualization online tools](#visualization-online-tools)

* [Visualization tools (timeline)](#visualization-tools-timeline)

* [Visualization tools](#visualization-tools)

* [Journals, Publications and Magazines](#journals-publications-and-magazines)

* [Other Awesome Lists](#other-awesome-lists)



## What is Data Journalism



*This part is for humans who are new to Data Journalism*



What makes data journalism different to the rest of journalism? Perhaps it is the new possibilities that open up when you combine the traditional ‘nose for news’ and ability to tell a compelling story, with the sheer scale and range of digital information now available. [Source: What is Data Journalism?](http://datajournalismhandbook.org/1.0/en/introduction_0.html)



More about Data-driven journalism [Wikipedia: Data-driven journalsim](https://en.wikipedia.org/wiki/Data-driven_journalism)



## Handbooks and books

 * [Data Journalism Handbook](http://datajournalismhandbook.org/)

 * [CIJ Data Journalism Book](http://www.tcij.org/sites/default/files/u4/Data%20Journalism%20Book.pdf)

 * [Data Journalism Heist](https://leanpub.com/DataJournalismHeist)

 * [Data + Design](https://infoactive.co/data-design)

 * [Finding Stories in Spreadsheets](https://leanpub.com/spreadsheetstories)

 * [Scraping for Journalists](https://leanpub.com/scrapingforjournalists)

 * [Organising an Online Investigation Team](https://leanpub.com/investigationteambook)

 * [The Functional Art](http://www.thefunctionalart.com/p/about-book.html)

 * [Facts are Sacred](http://www.theguardian.com/news/datablog/2013/apr/25/data-visualisation-data-journalism)

 * [The Information Capital](http://theinformationcapital.com/)

 * [Knowledge is beautiful](http://www.informationisbeautiful.net/2014/knowledge-is-beautiful/)



## Formal education

 * [Specialization in data @ Columbia Journalism School](http://www.journalism.columbia.edu/page/1077-specialization-in-data/936)

 * [Stanford Journalism Program. Data journalism and storytelling](http://journalism.stanford.edu/)

 * [Data journalism @ City University London](http://www.city.ac.uk/arts-social-sciences/modules/data-journalism-data)

 * [Training the Journalists of Tomorrow @ Tiburg University](https://www.tilburguniversity.edu/education/masters-programmes/data-journalism/)

 * [Data journalism in Russia, magister program @ High School of Economy](http://www.hse.ru/ma/datajourn/)



## MOOC's

 * [Learno.net data courses](http://learno.net/courses)

 * [Doing journalism with data](https://www.canvas.net/courses/doing-journalism-with-data)



## Data Sets

 * [World Bank data portal](http://data.worldbank.org)

 * [US Government open data portal](http://data.gov)

 * [UK Government open data portal](http://data.gov.uk)

  

## Web scraping

* [Scraping for Journalism: A Guide for Collecting Data](https://www.propublica.org/nerds/item/doc-dollars-guides-collecting-the-data)

* [Making data on the web useful: scraping](http://schoolofdata.org/handbook/courses/scraping/)

* [HTML Scraping Python Guide with lxml](http://docs.python-guide.org/en/latest/scenarios/scrape/)

* [Beginner’s guide to Web Scraping in Python using BeautifulSoup](http://www.analyticsvidhya.com/blog/2015/10/beginner-guide-web-scraping-beautiful-soup-python/)

* [A Guide to Web Scraping Tools](http://www.garethjames.net/a-guide-to-web-scrapping-tools/)

* [Web scraping course](https://www.udemy.com/scraping-and-data-mining-for-beginners-and-pros/)

* [Codeacademy | Web API Courses](https://www.codecademy.com/apis)

* [Chrome browser Scraper extension](https://chrome.google.com/webstore/detail/scraper/mbigbapnjcgaffohmbkdlecaccepngjd)

* [Kimono | Turn websites into structured APIs from your browser in seconds](https://www.kimonolabs.com/)

* [Import.io | Extract web data the easy way](https://www.import.io/)

* [ScrapingHub | Online scraping platform](http://scrapinghub.com/)

* [ParseHub | Turn dynamic websites into APIs](https://www.parsehub.com/)

* [Data-Miner.io | Online scraping tool and Chrome extension](https://data-miner.io/)

* [Diggernaut | Turn website content into datasets](https://www.diggernaut.com/)



## Facebook Accounts

 * [Data Driven Journalism](https://www.facebook.com/data.driven.journalism/)

 * [Data journalism blog](https://www.facebook.com/datajournalismblog)



## Twitter Accounts

* [Guardian Data](https://twitter.com/GuardianData)

* [Data Journalism Blog](https://twitter.com/Data_Blog)

* [Data Driven Journalsim](https://twitter.com/ddjournalism)

* [Simon Rogers @ Guardian Data Blog](https://twitter.com/smfrogers)

* [Daten Journalist](https://twitter.com/datenjournalist)

* [Paurl Bradshaw](https://twitter.com/paulbradshaw)

 



## Visualization Online Tools

 * [Canva](https://www.canva.com/create/infographics/)

 * [Charted](http://www.charted.co/)

 * [Data Illustrator](http://data-illustrator.com/)

 * [Datawrapper](https://www.datawrapper.de/)

 * [Datacopia](http://www.datacopia.com/)

 * [InfoActive](https://infoactive.co/)

 * [Infogr.am](https://infogr.am/)

 * [Piktochart](http://piktochart.com/)

 * [Plot.ly](http://plot.ly)

 * [Tableau Public](https://public.tableau.com)

 * [Venngage](https://venngage.com/)

  

## Visualization Tools (Timelines)

 * [Time Glider](http://timeglider.com/)  

 * [Tiki-Toki](http://www.tiki-toki.com/)

 * [Hstry](https://www.hstry.co/)

 * [Dipity](http://www.dipity.com/)

 * [Timeline JS3](https://timeline.knightlab.com/)

 

## Visualization Tools

 

 * [addepar](http://addepar.github.io/#/ember-charts/overview)

 * [amcharts](http://www.amcharts.com/)

 * [anychart](http://www.anychart.com/home/)

 * [bokeh](http://bokeh.pydata.org)

 * [capsidea](https://capsidea.com/)

 * [cartodb](http://cartodb.github.io/odyssey.js/)

 * [Cube](http://square.github.io/cube/)

 * [d3plus](http://d3plus.org/)

 * [Data-Driven Documents(D3js)](http://d3js.org/)

 * [datahero](https://datahero.com/)

 * [dygraphs](http://dygraphs.com/)

 * [ECharts](http://echarts.baidu.com/index-en.html)

 * [exhibit](http://www.simile-widgets.org/exhibit/)

 * [Gatherplot](http://www.gatherplot.org/)

 * [gephi](http://gephi.github.io/)

 * [ggplot2](http://ggplot2.org/)

 * [Glue](http://www.glueviz.org/en/latest/)

 * [Google Chart Gallery](https://developers.google.com/chart/interactive/docs/gallery)

 * [highcarts](http://www.highcharts.com/)

 * [import.io](https://import.io/)

 * [jqplot](http://www.jqplot.com/)

 * [Matplotlib](http://matplotlib.org/)

 * [NetworkX](https://networkx.github.io/) - High-productivity software for complex networks

 * [nvd3](http://nvd3.org/)

 * [Opendata-tools](http://opendata-tools.org/en/visualization/) - list of open source data visualization tools

 * [Openrefine](http://openrefine.org/)

 * [plot.ly](https://plot.ly/)

 * [r2d3](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/)

 * [raw](http://raw.densitydesign.org/)

 * [rcharts](http://rcharts.io/)

 * [techanjs](http://techanjs.org/)

 * [tenxer](http://tenxer.github.io/xcharts/)

 * [Timeline](http://timeline.knightlab.com/)

 * [variancecharts](https://variancecharts.com/index.html)

 * [vida](https://vida.io/)

 * [Wolframalpha](http://www.wolframalpha.com/)

 * [Wrangler](http://vis.stanford.edu/wrangler/)



## Journals, Publications and Magazines

 * [A short list of online articles and references on data journalism](http://www.smalldatajournalism.com/readings/)

 * [How to get started with GitHub for Dummies Journalists](http://www.interhacktives.com/2015/05/04/how-to-get-started-with-github-for-dummies-journalists/) 

 * [Data Driven Journalism](http://datadrivenjournalism.net/)

 * [Journalism and New media](https://cartodb.com/solutions/journalism/)



## Other resources

 * [MaryJo Webster's training materials](https://mjwebster.github.io/DataJ/)

 * [Global Data Journalists Directory](https://jplusplus.github.io/global-directory/)

 * [Periodic table of Visualization](http://www.visual-literacy.org/periodic_table/periodic_table.html)

 * [Chartmaker - comparison of data visualisation tools](http://chartmaker.visualisingdata.com)



## Other Awesome Lists



 - Other amazingly awesome lists can be found in the [awesome-awesomeness](https://github.com/bayandin/awesome-awesomeness) list.

 - [Awesome Machine Learning](https://github.com/josephmisiti/awesome-machine-learning) A curated list of awesome Machine Learning frameworks, libraries and software.

 - [lists](https://github.com/jnv/lists)

 - [awesome-dataviz](https://github.com/fasouto/awesome-dataviz)

 - [awesome-python](https://github.com/vinta/awesome-python)

 - [Data Science IPython Notebooks.](https://github.com/donnemartin/data-science-ipython-notebooks)

 - [awesome-r](https://github.com/qinwf/awesome-R)

 - [awesome-datasets](https://github.com/caesar0301/awesome-public-datasets). – An awesome list of high-quality open datasets in public domains

 - [awesome-opendata-rus](http://github.com/infoculture/awesome-opendata-rus) - An awesome list of open data in Russian language