“…regardless, look at how well my 401k is doing”

Python

by itself, it says very little than there are some (possibly) disproportionate impacts. As @memfree notes, there is a lot of overlap by population, but that doesn’t tell the whole story. There are some anomalies that need to be explored, and this map is just a preliminary analysis. Are there different living situations (e.g., prisons, long-term care facilities) whose populations are acting as a con-founder? I hope to keep exploring this.

There have been accusations that the purge process was conducted in a partisan manner, but there is little hard data to back up claims on either side. This work is an (initial) attempt to characterize who is impacted by looking at community demographics.

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You do build steel grain bins from the top, down, however

Deep sleep modes with a range of good interrupt handling is where I would start, but I don’t have any specific recommendations, unfortunately.