R

TSA Throughput with Scraping html Tables

I saw one of the smartest people I e-know (the one and only @hrbrmstr) post TSA’s daily airline passenger traffic numbers circa March 01, 2020 and later, and the corresponding numbers for the same dates albeit in 2019. The data source is an html table, and since I haven’t scraped html tables in a while, I wanted to get rid of the cobwebs. Surprisingly easy but then the TSA data source-page is a very clean setup.

Tracking COVID-19 in Ohio's Counties

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. They are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak. This is a map built with their data and updated (almost) daily to track progress in Ohio’s counties.

Initial Unemployment Insurance Claims Filed in Ohio's Counties

A few weeks ago I was bemoaning the fact that the state was not releasing the weekly county-level initial and continued unemployment insurance claims data in anything but an old pdf format. How old you ask? You know, the kind the Census Bureau gave up in the 1990s. Anyhow, turns out the PDFs could be scraped with relatively little pain; thank you {tabulizer}!! So here are the data, only the weeks in 2020 for now but the plan is to update this weekly through the crisis, and to go back over the years as well, at least until September/October 2017, the earliest data releases I can find.

Resident Population Change in Ohio

Now that the population change estimates are out, here is a quick peek at Ohio’s estimates. First up – the extent of gains and losses in our counties. No surprises here; Most of the Appalachian counties have seen population losses. Specifically, Appalachia lost 48,211 persons while the rest of the state gained 200,896 persons. The largest gains were in Franklin (146,768), Delaware (30,654), Warren (19,353), Hamilton (14,312) and Butler (14,243).

Poverty and Health Insurance in Appalachia

The Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) Program and the Small Area Health Insurance Estimates (SAHIE) Program are two of my favorite ‘go-to’ sources for small-area estimates. Both are easily grabbed via tidycensus so the first thing I’d like to do is explore county-level trends going as far back as is possible – 2008-2018 for SAHIE, 2006-2017 for all SAIPE estimates except for school-age (5 to 17 in families) poverty rate estimates that allow for longer comparisons (2005-2017).

Appalachia: A Profile in Numbers

The founding report of the Appalachian Regional Commission does a wonderful job of highlighting the state of affairs in Appalachia circa 1950 and 1960. The prose is not too shabby even if it careens every now and then into the romantic: “Graphs and tables can hardly relate the acutely personal story of a child in a remote valley, his horizon of opportunity limited to the enclosing hills; nor the despair of his father, who, idled by forces beyond his control and seeing no prospect of future employment, must live month in and month out with the vision of that child repeating his own history.

Opioid Encounters in Ohio Counties

The opioid crisis is an issue in most parts of the country and Ohio is no exception, with some of the highest numbers of Fentanyl encounters reported by law enforcement. Although one could, I suppose, try to identify county-level deaths due to drug overdoses via CDC Wonder, this is a quick look at the data provided by the Ohio Hospital Association’s Overdose Data Sharing Program.

Opportunity Youth in Ohio

A client needed state-level estimates of the percent of opportunity youth (defined either as 16-19 or 16-24 year-old persons who are neither in school nor employed) in each state plus Washington DC. The end result would be three years of estimates that matched the numbers put out by Measure of America’s yearly reports on the subject. I had used Anthony Damico’s fantastic repository Analyze Survey Data for Free for BRFSS, DHS, and other data but never with the Census Bureau’s Public Use Microdata Samples (PUMS) data.

Monitoring the Hocking River

It is yet another rainy day but not really since the Hocking River that meanders through our town is under flood-watch. Things must be bad enough else why would the University cancel all classes for Monday. To whit: “A forecast for heavy rains and high winds have resulted in a flood warning for Athens County beginning this weekend into Monday. Based on current forecasts, specific areas on campus may be impacted by flooding Sunday evening into Monday morning.

Peaks First Climbed in the Himalayas: 1909-2017

I’ve been itching to get back into the himal database and Elizabeth Hawley’s passing jolted me back into action. I wanted to start by looking at the peaks themselves, hoping this would give me a better understanding of the fields before I delve into the expedition data. We have data on 457 peaks, but only 377 are open and only 309 of these have been climbed. Information about the date of the summiting is missing for 3 peaks (we have the year and the month but not the day) so that drops the dataset down to 306 peaks.