![]() ![]() SQL lets you manage databases, while Javascript is the programming language of choice when it comes to presenting data in an interactive way so readers can enjoy scrollytelling or interact with the data. As data journalism becomes heavily embedded in the online world, data analysis becomes dependent on back-end and front-end development. While R and Python serve primarily as languages for processing data, newsrooms rely heavily on programming to present their data journalism pieces. In addition, with appealing libraries for data visualisation, both R and Python offer great ways to create appropriate charts while allowing for customisation and allowing the newsroom to define its own style. Once you have collected, cleaned and analysed your data in a programming environment, creating visualisations can improve the workflow. Both The Economist and The Times of London use R along with React The New York Times relies on D3.js The Washington Post uses a mix of languages and software, as is likely the case in many newsrooms right now. Yet many news organisations' data teams increasingly rely on programming to create their graphs. Creating charts that explain the story in your data can be done with Datawrapper, Tableau, Flourish, and other programmes. This is the stage where no-code journalists are likely to suffer the least: The list of powerful visualisation software is extensive and growing. As Basil Simon writes in the Data Journalism Handbook 2, there is a point "where data and code become companions." Given software limitations on the size of datasets - Excel has a limit of 1,048,576 rows by 16,384 columns in 2021 - navigating large datasets can only be achieved through programming. Whenever the volume of data is immense, coding makes the process of data cleaning faster, if not possible in the first place. Whether you are building a crawler to assemble data from multiple Web pages or collecting data from Twitter or the World Bank through their API, coding can help you become more resourceful and get around some typical obstacles to accessing data: you can source data that is not easily accessible, collect large amounts of it, and reduce the time it takes to compile it. This process can be highly facilitated by coding, such as extracting data from the web or obtaining it through an API. Whenever the data for your story is not immediately available, you need to compile it. The process usually consists of four moments: compile, clean, visualise, publish. The steps required to create a data journalism piece can vary from project to project, but we can generalise the data journalist's workflow. What does coding offer that data analysis software can't? Still, coding can be extremely powerful and give you a form of control and freedom unmatched by software. The software that covers the various aspects of a data journalist's workflow already exists, and it can save you the frustrating journey of hunting for coding errors and reading countless Stack Overflow threads. You can create graphics using Datawrapper, Tableau, or yet another in-house tool for data visualisation. ![]() You can be the type of data journalist who downloads a finished dataset, does all the data wrangling in Excel, OpenRefine, or a tool designed specifically for your newsroom. ![]() Let's start with the question of why: Why should a data journalist know how to code? While there are several benefits, the biggest one is that programming skills can expand the types of projects you can do. ![]() Is coding an essential skill for a data journalist? ![]()
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