Cumulative eBird Sightings in Allegheny County

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.

eBirding in Allegheny County

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.

Roughly Calculating Allegheny County Transit Efficiency

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.

Graphing Seasonality in Ebird Bird Sightings

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.

Visualizing Transit Connections Between Pittsburgh Census Tracts

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.

How Many Pittsburghers Cross the River to Get to Work

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.

Analyzing Commuter Patterns in Allegheny County

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.

Forecasting Healthy Ride Ridership With Prophet

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.

Residential Zoning in Pittsburgh

The New York Times recently published an article about zoning in U.S. cities, particularly single-unit detached residential housing. The article did not include Pittsburgh, so I downloaded the zone shapefile from the WPRDC and made my own map.

Map Census Data With R

This talk was presented on May 30th, 2019 at Code For Pittsburgh. Before we dive in, this presentation assumes that the user has basic familiarity with tidyverse, mainly dplyr.