My recommended tools for data journalism. Carefully selected and frequently used by myself. I categorized these tools in three phases of data journalism: Data finding, data cleaning and data visualisation.
- Write your own scraper in Ruby/Python or request data (read: pay someone to scrape).
- Plugin for Chrome browser to scrape web pages to Google Spreadsheets
- Find, play around and visualise data. Spreadsheet data in wikipedia form, uploaded by users. Also, a nice way to store your data.
- Transform documents to spreadsheets. Not perfect, but saves a lot of time.
- Essential software for each data journalist.
- Great tool for mass editting data. Not for calculations, but specifically data cleaning.
Mr. Data Converter
- Transform data from one format to another: HTML, XML, JSON, MySQL, Ruby, PHP, Python.
- What colors do you need to use? ColowBrewer categorizes color scales in sequential, diverging and qualitative color schemes.
- An extensive library for data visualisation. Keep in mind: a lot of programming.
- Visualizes data from XML to Flash or HTML5 graphics.
- Visualisation tool, especially for maps. Also for line, bar, pie graphs, scatter plots and network visualisations, but not great.
Fusion Tables Layer Wizard
- Want to optimize your Fusion Tables map, this is the tool. Generates an HTML document.
- Fast and easy networks visualisations
- Easy and fast charts made with the Google Charts API. Through Google Spreadsheets (embeddable charts) or the Charts Playground (self-hosted)
Google Maps Style Wizard
- Tool for styling a Google Map. Customize labels and colors.
- Vector-based library for drawing graphics. Not easyily learned.
- Essential for converting SHP files to KML’s. You need Fusion Tables to make this work