With ArcGIS Hub's Civic Analytics notebook series we will empower you with spatial and statistical analysis techniques to work with civic data using newly released ArcGIS Notebooks. The goal is to put together a collection of notebooks where we will address a particular question or topic using data science tools in Python, and to take it forward by inspiring a community of citizens to use these notebooks as a means to understand their local data and region better and share the results of their data analysis experiments to further this pursuit of building a data-informed community.
This week we start with notebooks that focus on exploring and understanding the spatial and temporal aspects of street crashes in Ottawa, Canada in 2018. We focus on fetching data and highlighting the distribution of crashes across space and time to gain a more visual perception of civic data beyond the usual tabular structure. We also have a guide to walk you through the process of finding and using data. Additionally, for those looking here is a great interactive Python tutorial and resource for the ArcGIS API for Python.
Click here to read more on our blog post.
Feel free to share your thoughts and results from your experiments with civic data from your local Hub in these notebooks!
