esridc / Indicator-Dashboard

A pythonic way to access and analyze initiative data and to build insightful infographics that convey a snapshot view of a city’s performance

Indicator-Dashboard

A pythonic way to access and analyze initiative data and to build insightful infographics that convey a snapshot view of a city’s performance. To learn more, click here

Motivation

To ease into the process of making data open and working with open data, we have put together a recommended list of key datasets or Indicators that, if provided and configured, can generate dashboards and meaningful analytics.

Hub's Indicators for Governments can be conceptually classified into the following three categories:

• Measures are data measured over space and time that indicate trends, outliers and comparisons. Eg. Crime, Street crashes, parking violation

• Places are important locations that support common public service. Eg. Schools, Hospitals, Transit Stops

• Boundaries are distinct areas that denote an administrative, operational, or conceptual limit. Eg. Neighborhoods, Census Tracts, Counties

Categorizing data into these explanatory types helps generalize them to understand and analyze them appropriately.

For instance, a temporal analysis applies to a Measure, whereas it is critical to observe how accessible a Place is to the areas around it. A Boundary, on the other hand, provides a great sub-division to aggregate your Measures/Places against and to notice their effect on demographics. Click here to see an example

Indicator type and analytics generated

Indicator	Attribute	Analytic
Measure	time	histogram, weekday-weekend pie chart
	category1	bar chart
	category2	pie chart
		heat map
Place	value	Average count (text statistic)
	category1	bar chart
	category2	pie chart
		map of locations
Boundary	value1,value2	scatter plot
	category1	pie chart
		Map of enriched boundary

Getting started with it:

1. Clone this Github Repository to get a copy of the dashboard scripts we have put together.

2. Customize the notebook by providing the relevant initiative id, sign it to ArcGIS with your credentials and make calls to specific functions such as measure_dashboard(), measure_place() or measure_boundary() based on the particular indicator classification and watch the analytics unfold.

Want to Contribute?

Make a Pull Rquest to this repository with the changes you propose.

To recommend enhancements or report issues, click here