1-2 Understand Technical Tools
In order to begin developing a data visualization to solve a particular need, you must understand the technical tools at your disposal.
There are numerous ways to collect, process, and visualize data. Here, we introduce three popular tools — spreadsheets, Python notebooks, and web apps. All three options provide powerful features, but each of them offer particular strengths to consider for your development. These tools can be used in isolation or combined in a workflow. In order to better understand what is technically feasible for you project, complete each of these exercises to prepare you for creating a proposed concept.
1 Spreadsheets
Spreadsheets are the Swiss Army Knives of data, providing a quick entry point to processing and visualizing data.
Complete this spreadsheet exercise to build a practice visualization.
Deliverable: Export your Google Drawing (Finished Visualization) as a PDF and provide a shareable link to your Google sheets file.
2 Python Notebooks
Python notebooks are increasingly popular choice for data scientists with many code libraries that make coding with data very efficient and powerful.
Complete this Python notebook exercise to build a practice visualization.
Deliverable: Export your notebook as a PDF and provide a shareable link to your Python Notebook in Google Colab.
3 Web Apps
Web apps provide a universal way to share data visualizations through a common browser and can be dynamically updated with live data.
Complete this web app tutorial to build a practice visualization using the CxD Javascript Library for Data Visualization. Once you have completed the tutorial, implement two chart modifications based on the chart examples, two SQL modifications based on the SQL examples, and one layout modification based on the dashboard layout examples.
Deliverable: Provide a link to your working web app visualization on Replit.com or similar platform.
For reference: Open Sources of Data
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