Google Data Studio
A Beginner’s Guide to Data Visualization
Google data studio is a free visualization tool used to build reports. Visualization is one of the most powerful analytical tools in the field of data science. Building reports can be tricky to dive into, but everyone has to start somewhere. Being familiar with your data and drafting a plan for what graphics you want out of Google Data Studio can make you master this tool in an efficient manner.
In this blog, I will be walking through the basics of Google Data Studio. Use the links below to follow along!
Google Data Studio Report for United States Homicides: https://datastudio.google.com/reporting/23874e8e-5087-4265-b5ec-9df45c592582
Homicide Dataset: https://www.kaggle.com/murderaccountability/homicide-reports
1. Choose a template or start with a blank report.
When choosing a template, be sure to go with one that matches the type of data you want to connect with. This tool provides plenty of templates so if you for example are making visualizations on financial data, choosing that template can give you a specific guide.
2. Connect to a data source, and select the proper data types for each of your fields.
There are over 300 data sources that you can connect and build reports for. Some of these sources include MySQL, Google Could Storage, or a CSV file. Most data source connectors can be refreshing — if the data is updated in Google Could Storage, you can refresh and get new values! There is no need to reimport your data.
Click on the ‘Add Data’ on the tool bar.
For the homicide data, you can see a couple of fields and the data type it is given. Putting City as the data type city rather than text will allow you to build maps and plot the city data.
3. Begin to play around with the data.
On the tool bar, begin by selecting ‘Add a chart’ and choose a table. This will allow you to take a look at your data. The Dimension is what you want your dataframe to be grouped by. In this example, it is grouping by the city, and then the state. The Metric in this example is giving the total count of records for the city and state. We could make the metric ‘Perpetrator Age’, and set it to the average in order to get the average age by city and state.
Trial and error is going to happen. But that’s okay! It is important to be familiar with your data before being able to manipulate it perfectly. You may not know what you want to get out of a visualization just yet, but adjusting a table can get you started!
Once you have gotten a sense of what is in the data source, choose a new visualization — there are plenty of options to choose from!
For this Visualization, the dimension is Weapon and the Metric is record count.
If we want to take it one step further, we can add a breakdown dimension.
This bar chart is presenting the same data as above, but it includes a breakdown on whether or not the Crime was solved. The legend indicates the breakdown dimension.
4. Style your visualizations!
There are plenty of options when it comes to styling the graphics in Google Data Studio in the style tab. You can adjust your bar charts to be side-by-side or stacked, horizontal or vertical, and more. You can adjust the axes and add labels.
When presenting these visualizations to a client, it is important that anyone could look at report and understand what each graph is trying to convey. Having proper axes labels, chart title, and a cohesive color scheme can help you look more professional.
Thank you, and good luck visualizing!
