Election Data Analyzer

Then there is the case of a non profit that does needle exchange. 74 people registered here. Again, the only way you would see this is boots on the ground canvassing or using the mapping tool street view then drilling into the name of the institution. I can't take anymore. I have completed looking at the top 20 address for 1/3 of the counties I am examining. Rental homes look like a real problem. Many many instancs of 8, 10, 12 voters registered at a house which I assume is a rental. Not all are Active but even then, I wonder how long it takes to get this cleaned up after someone moves?

I am sorry to say I just found my first instance of 33 people registered to a urban university parking lot. Triple checked. The EDA mapping tool found it for me. I just had to grind through the list one by one. Mixture of D, R and U both Active and Inactive. There are many other address listed than have apt #'s listed at the same address. So what is happeneing here is that people are using a general address of the university and not listing a unit number or apartment number or a specific dorm location. Does that make sense? How can that be permitted by law? Is this a wide spread practice all over the US? If we are mailing ballots, how does USPS know where to deliver? Most of the status on the mailed in ballot are "undeliverable" or "failed to vote" or "returned mail". What happens to those ballots? That will require more digging to figure that out. Can reasonable people agree that mainling ballots creates these sorts of confusion? Remeber, all 3 parties are listed above, this is not a partisan issue. Very sad state of affairs.

In v3.7 which is soon to drop, there is a new table and series of charts I am testing out to see if it yields anything useful. I won't know until users across multiple states try it out. But here is the idea. Let U=sum of Unaffiliated. Let D=sum of DEM and R=sum of Rep. Now specify the SUM range to be whatever you want. I looked at 1/1/20-11/6/20. U, D, R are the # of daily registrations. Now, take the formula U/(D+R) and calculate a ratio for each county. In my case, I did that for 12 counties. The counties are red, blue and purple. In ALL cases the ratio calculated out to be between ~ 0.95 to 1.1. What does this mean? Is it simply a reflection of the increased number U's in my state? I don't know, but it popped out to me. I will be meeting with a math genius soon about this and maybe he will say it is a big "nothing burger" or maybe not. I'll let you know either way. Looking forward to seeing what other produce in their states.

My subscribers are awesome resources....check this one out from a Marine https://www.vote.org/voter-registration-deadlines/

Sorry, I accidentally left out the age group above 53 on the chart above, updated here.

Then, I looked at the Reg Dates and was scratching my head...So, I did a bit of a quick case study. In exploring the map further, I discovered this was a rent controlled newer apartment complex. It is what it is. I am not criticizing that. I am going to just leave this data here and see if people think this might be a good place to canvas or not? I have not decided. What do you think?

I had intended on spending time working on my state wide report of the 12 most populous counties and giving the posts here a break, but then, I found a rabbit hole. What triggered it was in the EDA last name analyzer table, someone popped up with a 29 character last name! Wow! A new record in my research. I will scramble the last name but you will get the idea: "Sitting Deer LightInTheHouse". Again, this is scrambled. This person has 42 characters in the first, middle and last....(imagine filling out a form with that name?) So then, I went to the mapping tool and located this address by filtering on the characters in last name field. Then using the Excel wildcard character (*), searched again using a filter like this "Address*". And a bunch of people showed up, no problem. It is a large apartment complex on the map, makes sense so far……

Hey folks, I have standardized these new charts into EDA that look at the ratios and count data I posted this morning on the case study above. This will be dropped as v3.6a this weekend.

From the FAQ pinned.

My subscribers are awesome! Lori suggested this program for massive .csv file splits. I have not used it yet, but it sounds promising. Here is what she said: There is an easy fix for the super large excel files. You can download a free program called Free Huge CSV Splitter and after you’ve downloaded the large csv file with the information you want, you just link to that and tell it how many lines you want per file (I put in 500,000) and it will split it up for you then you can easily open in excel. Just downloaded and did it myself. It worked beautifully. You don’t appear to be able to choose your output file so mine ended up in documents/extracted files/. You can have just over a million lines on a worksheet and 225 worksheets in a workbook in excel.

Finally, there is the chart itself. Nice sinusoidal curve until right after election day. So that's your home work for today EDA fans. You can do this too. The data is sitting there for you. It is not hard.

Now this table is a bit hard to explain but it something I built on the free form sheets. This is a COUNT of the number of times an integer ratio resulted from the formula U / D, or U / R or U / (D+R). As you can see there were 108 days in 2020 where the relationship between U / D resulted in an integer. Almost twice as much as the others. Weird right? Maybe, maybe not.

This is from the chart I posted yesterday. Only one person saw what I saw, which is interesting. What one person thinks is obvious doesn't make it so. To me, the profiles of these curves are related. Look at how the yellow hump patterns are almost the same as the blue. I have not done a statistical analysis on this, I am just looking at it. Yellow is unaffiliated. Blue is DEM.

This is a ratio of U / (D+R). The top line you can think of as the overall history. The bottom line is from 2020. The 2020 ratio is effectively 1.0.

This is simply the pivot of party affiliation of the entire registration history from the 1940s onward. I added the % breakdown.

Hey folks, I am going to post this analysis I did of the same county described above. I'll post the total analysis here, then explain each piece. All of this data comes from EDA. I did use the free form sheets to build some additional tables and charts which you can also do. I am simply going to present the data without comment. Interested in what you think. Is this something to dig further on or a big nothing burger? You decide.

When signing up with USEIP, please put your Telegram handle in this “What Else” box and make reference to EDA. This will permit your placement into the private drop group for v3.6. For those who may have signed up today already and not done this, no worries. Just leave a comment here or DM me and I will resolve it. Thanks for your patience as we work this out.