The examples you gave are in m/d/y format though, and DATEVALUE() parses your examples correctly into Jan 15th, 2024 and January 3rd, 2024.

DATEVALUE() parses ambiguous short date formats (e.g. 1/3/24) using the short date format specified in the Region settings of Windows Control Panel. So if you want to parse d/m/y format, you can try changing the settings there.

https://www.naftaliharris.com/blog/steinviz/

https://www.youtube.com/watch?v=cUqoHQDinCM (this video actually references the original post)

My takeaway is that the volume of points which get worse as they are pulled towards point P exists in some region R. As the number of dimensions increase, region R's volume shrinks as a % of the total cloud volume, making it much more unlikely that a sample is pulled from that region. In other words, you are more likely to sample points which move closer to the center than move away, which is why the estimator is an improvement on average.

Also, the Inflation Reduction Act introduced a 1% tax on stock buybacks starting in 2023[1], so there is still in some sense a tax impact on the remaining shareholders.

[0]https://www.apple.com/newsroom/2024/05/apple-reports-second-...

[1]https://www.irs.gov/newsroom/treasury-and-irs-announce-new-r...

Is this actually true? It is not clear to me that pi necessarily contains every possible sub-sequence.

Absolutely. There could be other factors that are counteracting the effect, including those within the ACA itself since the bill contains many changes to healthcare, not just the restriction on medical loss ratios.

If this perverse incentive were true, then you would expect the medical care costs to rapidly increase after the passage of ACA, but medical trend has actually slowed down since then[0] [1].

You can also look at the total dollar spend on hospital and medical expenses for the entire health insurance industry [2]. After the passage of ACA, there was a large increase in medical spend as more people obtained insurance coverage, but the increase in medical expenses year over year has settled back into the 5% range, which doesn't seem that perverse.

[0]https://www.statista.com/statistics/720767/medical-cost-tren...

[1]https://www.pwc.com/us/en/industries/health-industries/libra...

[2]https://content.naic.org/sites/default/files/2021-Annual-Hea...

>Buying a policy to file a claim for an event that already happened is called fraud, and while it does happen, it's generally pretty easy for insurers to detect and prevent.

Detection has underwriting costs associated with it. Investigating whether you knowingly purchased an insurance policy with an incoming claim is not something that is automated. By default a claims made policy will prevent the issue in the first place by resetting what is known as the retroactive date. This causes the lapse in coverage the OP was referring to.

There are specialty insurers who will allow you to explain extenuating circumstances, and/or set retroactive dates prior to the effective date of the first claims-made policy. You obviously pay for the additional risk this poses to the insurer though.

This is to protect the insurer against adverse selection. Errors and omissions policies are typically on a "claims-made" basis, which means they cover claims that were filed against you during the policy period, as opposed to incidents occurring during the policy period.

It is assumed that if you let your policy lapse and then buy a new policy, that you know that there is some incoming claim against you for which you need protection from.

I think part of the problem is that any scripting language rolled directly into Excel will be expected to keep backwards compatibility. Microsoft doesn't have full control over Python/JS, and they would like to avoid issues such as the changeover from Python 2 to 3.

Microsoft could implement its own fork of those languages, but is that what customers actually want?

-You still need to enumerate and label each new column and their types. This particular problem is fixed by crosstabN().

-You need to know upfront how many columns are created before performing the pivot. In the context of data analysis, this is often dynamic or unknown.

-The input to the function is not a dataframe, but a text string that generates the pre-pivot results. This means your analysis up to this point needs to be converted into a string. Not only does this disrupt the flow of an analysis, you also have to worry about escape characters in your string.

-It is not standard across SQL dialects. This function is specific to Postgres, and other dialects have their own version of this function with their own limitations.

The article contains several examples like this where SQL is much more verbose and brittle than the equivalent pandas code.

SQL is very useful, but there are some data manipulations which are much easier to perform in pandas/dplyr/data.table than in SQL. For example, the article discusses how to perform a pivot table, which takes data in a "long" format, and makes it "wider".

In the article, the pandas version is:

>pd.pivot_table(df, values='name', index='role', columns='department', aggfunc='count')

Compared to the SQL version:

>SELECT role, SUM(CASE department WHEN 'R&D' THEN 1 ELSE 0 END) as "R&D", SUM(CASE department WHEN 'Sales' THEN 1 ELSE 0 END) as "Sales" FROM emp GROUP BY role;

Not only does the SQL code require you to know up front how many distinct columns you are creating, it requires you to write a line out for each new column. This is okay in simple cases, but is untenable when you are pivoting on a column with hundreds or more distinct values, such as dates or zip codes.

There are some SQL dialects which provide pivot functions like in pandas, but they are not universal.

There are other examples in the article where the SQL code is much longer and less flexible, such as binning, where the bins are hardcoded into the query.

>Again, perhaps my view is biased because I grew up with the pixelated games of old. Still, I'd like to assign the excitement of the early 3d titles more to the novelty (at the time) than from the fidelity of the graphics. I think the pixel art style will (or already does) have much more staying power.

I happen to agree that early 3d games like PS1/N64 look rather ugly, but nostalgia is very powerful, and retro low poly models is now its own aesthetic [0]. Like with pixel art, artists will take liberties with what was actually capable with hardware at the time, but people who grew up with the style will probably appreciate it more.

[0]https://www.gamasutra.com/view/news/321754/Designing_a_demak...

>But insiders claim that it will allow the founding companies to implement ideas from the project on their own, tailoring them to the specific needs of their employees, who are mostly concentrated in different cities.

Medical services is mostly a localized service, so each city is its own individual market. As large as Amazon, JPMorgan, and Berkshire are, their employees are spread out geographically, and even in their headquarter cities, they do not represent a significant number of people negotiating for medical services. Without a way to control the actual medical service supply (i.e. doctors and hospitals), their programs will have to negotiate at market rates, meaning there really is no way to achieve significant savings.

Amazon released their pill pack service, which helps because drugs can be shipped across the country, so there are efficiencies to be gained there. However, drug costs are still a smaller percentage of overall costs [0], albeit growing.

[0]https://www.ama-assn.org/about/research/trends-health-care-s...

>1) Increase number of subscribers. Possible to do, but the market is pretty saturated.

>2) Raise prices of healthcare overall. 20% of larger costs is more than 20% of smaller costs.

The 20% profit margin also has to cover the insurer's operating expenses. After covering the costs, an insurer typically makes 2-3% in profit. Also, the insurance industry in aggregate is typically paying 85%-86% of premiums as medical services, so they still have incentive to negotiate prices with hospitals[0].

The insurance industry is likely to make a greater profit in 2020 due to the pandemic. Consumers have deferred a lot of their medical procedures, but their premiums have stayed the same.

[0]https://content.naic.org/sites/default/files/inline-files/20...

Note the new transparency rule only affects hospitals, so the new rule won't cover services performed at local doctor's offices or clinics.

There will be several knock-on effects where the overall impact is unknown:

1. The transparency rule not only reveals prices to consumers, but also to other insurance companies and other hospitals. Since these price arrangements were typically conducted in private, this will impact negotiations between insurers and hospitals in competitive markets, which are typically in major cities. This is likely to force outliers on both the cheap end and expensive end to bring their rates closer to market. To the extent that either the hospital or the insurer cannot bring their rates closer to market, this may accelerate consolidation of hospitals into larger networks to improve negotiating power, and/or cause smaller insurers to drop hospitals from their network.

2. Since the transparency list is not comprehensive, and not all medical services are shoppable (i.e. scheduled in advanced, typically non life-threatening), this may cause hospitals to shift costs to services that consumers have no control over, meaning the emergency and unlisted procedures. It will take a few years for hospitals to understand the impact the rule has on their bottom line.

[0]https://en.wikipedia.org/wiki/Consumer-driven_healthcare

It lists side-by-side differences in hardcoded values, formula changes, calculated value changes, and even changes in VBA code. The list of changes can then be dumped out to a text file.

Default Excel installations also include the Inquire add-in which allows you to perform the comparison within Excel itself.

[0] https://support.microsoft.com/en-us/office/compare-two-versi...

[0]https://ncase.me/trust/

Word allows you to adjust the indentation on numbered lists so that the text in a paragraph is flush with the left margin. In Word 365 there are at least two ways to do this:

1. View -> Show -> [check Ruler] -> [Adjust the indentation on the ruler]

2. Layout -> Paragraph -> [click lower right arrow] Paragraph Settings -> Indentation -> change Special from (hanging) to (none), or change the "By:" value to 0

So the author's motivating example doesn't seem to be a particularly fair criticism of Word.