6 tools freelancers should know to better execute data stories and presentations


The world of data journalism can be daunting to many. However, anyone can present and produce a data journalism story, if they are able to grasp the right concepts.

For those new to data journalism, and even seasoned journalists looking to start reporting with data, these six tools can help you better execute your stories and elevate your pitches to editors:

Coding is a necessary evil

Having a coding language in your back pocket is crucial. Even the most basic coding knowledge can impact your work by allowing you to move away from simple spreadsheets, which, although commonly used in data journalism, are not preferred for a in-depth analysis because they cannot process so much information.

Coding will allow you to manipulate your data more easily. It’s rare that a data set is completely clean or exactly what you need. Being able to quickly clean up and comb through even the smallest files can solve some of the biggest headaches.

Learning to code can also open doors to things like web scraping and machine learning, two skills that can enhance your work. Although these techniques are not simple, they can be learned.

Not all coding languages ​​are created equal. Python is the easiest and most flexible language to learn. This language is also free and can be learned much faster than R or C++. Another benefit of Python is that it’s easier to find answers online to error codes when they occur, and offers more free help through easily searchable online forums.

It’s important to know how to visualize your stories, even if you don’t plan to use them more

Editors need to see what your data looks like, so even if you don’t plan on having visualizations in your story, being able to visually represent the information you’ll be using will only strengthen a pitch. It also shows the editor your understanding of the story and the data behind it.

The most commonly used visualization tool is Datawrapper, a free platform that makes it easy to transfer data. It’s easy to learn and can be used to create everything from simple graphs to more complex maps. Datawrapper uses basic HTML, but provides guides on how to write HTML in its interface.

Putting your datawrapper charts into Adobe software can also elevate the charts, but it will get trickier. Adobe offers free trials, which can be used to determine if paying for a subscription is worth it. Since Adobe is harder to learn than Datawrapper, it’s best used as an add-on unless it’s being run for a project, rather than a pitch.

Colors matter in visualizations, even in drafts

That art class you took in high school is extremely beneficial when designing data visualizations.

Colors are a crucial tool in data visualization because of how our brain works. We understand colors as another piece of information that can either effectively represent information or completely distort data. Everything down to color opacity can affect a reader’s understanding of the data they are viewing.

Colors like gray, white, or black should always be used sparingly or when trying to steer the reader to a specific data point. It is easy to understand how to use colors and it is extremely important.

There are several codes that can produce colors, such as Hex, RGB, and HTML. These codes are used to tell the computer exactly which of millions of colors and tints to choose, along with the most commonly used HTML code. You don’t have to memorize the six-digit codes for each color, just know that they exist, especially if you’re trying to match an exact color or match colors in different data visualizations.

In order to obtain a color code, there are several online tools to use.st. HTML Color Codes.com is a useful color code generator because it’s free, but there are many more. Getting familiar with a few schemes and having a few presets that you enjoy will come in handy in the long run.

The way you approach a story means everything

When trying to present a story, think about the finished product before the data. Unlike a typical story, where you can create the article from scratch, data reports rely more on your abilities to work with available data than on how much information a set has.

Although there are thousands of databases available to you, you will want to know how you plan to use a dataset before using it. This will help you gauge your abilities before you find a brilliant dataset that you want to do amazing things with, but might be too awkward or difficult to use.

To do this, define a thesis that you plan to try to test and how you will go about it. Create a storyboard that shows how you want to test this and what possible data is available. Then find your data and start your interviews.

Using a tool like Trello will help you with this. It’s free for personal use, but not for teams.

Asking for data can be your best friend or your biggest enemy

Requesting data from a government entity or organization can be a great way to get a story, but it comes with all the additional issues that any typical document request would pose. This is especially true with datasets that may be unnecessarily messy.

It is important to realize that while you may be requesting very specific data in a specific format, the data may not be completely usable. Spending that time requesting the data and then waiting to receive it can be costly, especially when you’re self-employed.

Instead of asking for data, finding open data online can be the most interesting. For the United States, most states have an open data website that has almost everything you need without having to go through a FOIA request.

It is important to have a backlog of data, even if you do not plan to continue data reporting

For journalists who are not seasoned data gurus, having datasets in hand and ready to go is essential. All datajournalists keep them, and having their own personal library is necessary.

Creating a free Github account to use as a library for your data can be useful to use as a reference. It can also build your portfolio and serve as a separate website for potential employers to see what you’ve been up to.

Photo by Markus Spiske on Unsplash.


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