I recently ran across the U.S. Census Bureau page for state-to-state migration flows. There’s a lot of interesting analyses that can be done with a dataset like this. Unfortunately, when I opened up the .
In this post, I use k-means clustering to identify clusters of bird species based on frequency of observations per month. I use bird sightings in Allegheny County from eBird.
This will be a quick post on cumulative bird observations in Allegheny County. Cumulative graphs show overall trends, seasonality, and quirks in how the data was recorded. They are also fun to turn into animated gifs with gganimate.
In this post I will do some exploratory analysis on eBird data. I’ve picked up birdwatching as a hobby during quarantine, and eBird has a ton of cool data on bird sightings.
As part my work on transit lines in Allegheny County, I am interested in which transit lines are most efficient, in terms of residents and jobs served. This is possible with the Port Authority transit line datasets hosted on the WPRDC and data from the Census.
Over the winter I became interested in birding. Sitting in your back yard doing nothing but watching birds fly around is quite relaxing. Naturally I am looking for ways to optimize and quantify this relaxing activity.
In this post I will use transit line and stop data from the WPRDC to map connections between census tracts. I access the census data via {tidycensus}, which contains information about the commuter connections between census tracts.
This post focuses on how many rivers Pittsburghers cross to get to work. I use the U.S. Census Bureau LEHD Origin-Destination Employment Statistics (LODES) dataset to draw lines between “home” census tracts and “work” census tracts, and then count how many “commuter lines” intersect with the 3 main rivers in Pittsburgh.
Note: high-res images of the main graphs from this post are available here, here, here, and here.
In this post I will use networks plots to analyze patterns of commuters in Allegheny County.
This post is about predicting demand for the Healthy Ride bike system in Pittsburgh. I wanted to try out Facebook’s prophet package and try to do some time series forecasting.