Track Economic Development

Analyze open data using predictive time series analysis

Time Series Analysis

This tool analyzes time series data using Socrata Open Government data on building permits to identify development trends in various cities.

Data Source

Analysis

Filter 1

Filter 2

How It Works

The world runs on data. Often times the effort to acquire fresh data, analyze it, and deploy live analysis can be a challenge.

Tools Used

Source Data

We use an algorithm to access Socrata’s API.

Once we’ve retrieved the data, we aggregate it by total number of permits issued per month, and plot it. To make the graph clearer, it sometimes helps to smooth or denoise the data. There are a number of ways to do this, with moving averages being the most popular. The most intuitive is the Simple Moving Average algorithm, which replaces each point by the average of itself and some number of the preceding points (default is 3).

Takeaway

While these techniques are available in a number of places, the secret here is that Algorithmia provides a simple, composable, and fully automated API. Once your data is connected to Algorithmia, (like the data provided by Socrata), you don’t have to waste precious time writing and working kinks out of your own. On the other hand, if something existing gets done better, the compositional nature of Algorithmia will allow you to swap out pieces of a pipeline seamlessly. When someone comes up with a better outlier detector, then upgrading a pipeline like the one above can be literally just a few keystrokes away.

Built For Developers

A simple, scalable API for machine intelligence

SAMPLE INPUT

var input = [[0,1,2,3,4,5,6,7,8,9,10],5,2];
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://timeseries/Forecast/0.2.0")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });
  

SAMPLE OUTPUT

[11, 12, 13, 14, 15]
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