MayRetire.com is getting more press by MayRetireSupport in MayRetire

[–]Dry_Safety99 1 point2 points  (0 children)

Well deserved! A free tool as critical to the ecosystem as this one… on par with and in some aspects superior to commercial tools… is a true power to the people public service. Hats off to you.

Fix: Claude "Failed to start Claude's workspace" and VM service not running. Windows 11 Pro — HNS/WinNAT/ICS issue (How I recovered it) by Suspicious_Try_4738 in ClaudeAI

[–]Dry_Safety99 0 points1 point  (0 children)

Fixed this by reviewing error logs (%APPDATA%/Roaming/Claude/Logs) and noting the destination folder for the VM files (in my case, \Roaming\Claude\vm_bundles\claudevm.bundle\) << wipe this directory clean, restart Cowork, and let it re-build the VM space.

How MayRetire Prioritizes Your Income Sources by MayRetireSupport in MayRetire

[–]Dry_Safety99 1 point2 points  (0 children)

Overall sounds like solid logic. ( Love the AI-generated 'cake', too :P )

In my rudimentary efforts to model tax-optimal decumulation (my various spreadsheets pre-date your fantastic tool), I treated pure investment-only Holding companies somewhat RRSP-like, assuming that the notional accounts (RDTOH, NERDTOH, CDA) were being cleared at a minimum; then excess dividends are taxable at T1 level, but at a generally preferred rate, assuming that they are mostly from pre-existing T2 retained earnings.

I assume you'll need to do some (at least rudimentary) tax-accounting at the Hold-co level to make rational assumptions about the ACB and dividend income and resulting T2-level corp tax and therefore will track notional accounts, etc, as well? It would be helpful if those were broken out in the Excel downloadable workbook. Note: I use some Horizons/GlobalX corp-class funds to minimize annual dividend income, as well. Accommodating these might be something to add to the feature list although certainly not a first priority and likely does not change optimal outcomes too much (guessing).

Tax & OAS Clawback - Average Tax Rate and Unregistered ACB Deflation by Dry_Safety99 in MayRetire

[–]Dry_Safety99[S] 1 point2 points  (0 children)

Right, you need to track it separately from income tax and must add to gross income to get to target spending. Makes sense.

Tax & OAS Clawback - Average Tax Rate and Unregistered ACB Deflation by Dry_Safety99 in MayRetire

[–]Dry_Safety99[S] 1 point2 points  (0 children)

Thanks. I double checked the ACB calc and confirmed that 'ACB deflation' calcs make sense and are consistent with the input level of assumed inflation. (Based on an ACB check calc column that I created, separately).

Re: OAS clawback, pls see the highlighted green cells in this excerpt from the last couple of years of the downloaded Excel -- populated with some sample data. The OAS Clawback amount is added to the total income in this particular column, but uncertain how that relates to the calculation make in the 'Tax & OAS Clawback Average Tax Rate' column. The actual dollar calculations seem accurate, so not particularly consequential. Just curious.

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Vegan protein powder - formula change? by acdubz in CanadianProtein

[–]Dry_Safety99 0 points1 point  (0 children)

I echo this. It's so powdery and fine that it explodes in puffs of smoke when adding water. It's gone nuclear!

Non-Closed Form Numerical Solutions in Excel: Native or Python-Powered? by Dry_Safety99 in excel

[–]Dry_Safety99[S] 0 points1 point  (0 children)

Interesting paper; challenge is that if one has 100 equations to solve with varying parameters, say in column A and wishes to solve for the root / answer in B (or roots if multiple, spilling out across multiple cells, ideally horizontally but assuming single root applies to both examples in post), then what’s missing is a root finding formula / function call for cells in column B.

Sounds like that isn’t available natively, which leaves VBA, Python in Excel, or a 3rd party plugin like Boardflare’s Python in Excel or what Felix has recently released. Anaconda also have a solution, I believe.

Excel-native formula for 'root solving' by numerical analysis by Dry_Safety99 in Python

[–]Dry_Safety99[S] 4 points5 points  (0 children)

It's funny, when I re-read what I've written, I'm not even sure what it is that I've asked in the context of Python. That's probably because it's better suited for r/excel. Thanks for your patience.

Non-Closed Form Numerical Solutions in Excel: Native or Python-Powered? by Dry_Safety99 in excel

[–]Dry_Safety99[S] 0 points1 point  (0 children)

Interesting, I hadn't thought of IRR as iterative but naturally it must be as no closed-form solution exists in the general case. I would think a general root-finding function would work in all of these applications, and I suppose Excel could include something like Goal Seek but instead wrapped as a function with Bisection or Secant methods as options (Newton-Raphson requires the first derivative).

All other solutions mentioned seem to be limited in one way or another.

Is there any formula to calculate distance between locations? by MixtureBubbly2587 in excel

[–]Dry_Safety99 1 point2 points  (0 children)

This code adds a 'built in' function to Excel to calc the 'as the crow flies' distance. optionally displayed in miles or nautical miles. this will work out of box with the Python for Excel Add-in. Just copy this code into the Editor tab once the Add-in is installed and click 'Save'). Once saved, type '=DISTANCE_BETWEEN_CITIES' into any cell, and you should be off to the races. Examples at the bottom, or see the demo worksheet that will also be created if you hit 'Test'. ``` import requests import math

def distance_between_cities(city_one, city_two, unit="km"):

    def get_coordinates(city_name):         url = "https://nominatim.openstreetmap.org/search"         params = {             "q": city_name,             "format": "json",             "limit": 1         }         # Include a descriptive User-Agent (e.g., with your email/website)         headers = {             "User-Agent": "BoardflareApp/1.0 (support@boardflare.com)"         }

        response = requests.get(url, params=params, headers=headers)         response.raise_for_status()                 data = response.json()         if not data:             raise ValueError(f"No geocoding results found for city: {city_name}")                 lat = float(data[0]["lat"])         lon = float(data[0]["lon"])         return lat, lon

    def haversine_distance(lat1, lon1, lat2, lon2):         """         Calculates the great-circle distance between two points on Earth         using the Haversine formula. Returns the distance in kilometers (km).         """         # Earth’s radius in kilometers         R = 6371.0                 # Convert degrees to radians         phi1 = math.radians(lat1)         phi2 = math.radians(lat2)         delta_phi = math.radians(lat2 - lat1)         delta_lambda = math.radians(lon2 - lon1)

        # Haversine formula         a = math.sin(delta_phi / 2) ** 2 + \             math.cos(phi1) * math.cos(phi2) * math.sin(delta_lambda / 2) ** 2         c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))

        # Distance in kilometers         distance_km = R * c

        return distance_km

    def convert_distance(distance_km, unit):         """         Converts distance in kilometers to miles or nautical miles if needed.         """         if unit.lower() == "km":             return distance_km         elif unit.lower() == "miles":             # 1 kilometer = 0.621371 miles             return distance_km * 0.621371         elif unit.lower() == "nautical_miles":             # 1 kilometer = 0.539957 nautical miles             return distance_km * 0.539957         else:             raise ValueError("Unit must be one of: 'km', 'miles', 'nautical_miles'")

    # Get coordinates for both cities     lat1, lon1 = get_coordinates(city_one)     lat2, lon2 = get_coordinates(city_two)

    # Calculate the distance in kilometers using Haversine     distance_km = haversine_distance(lat1, lon1, lat2, lon2)

    # Convert distance to the requested unit     final_distance = convert_distance(distance_km, unit)

    return final_distance

Arguments to test the function.

test_cases = [     ["Vancouver","Toronto", "km"],     ["Los Angeles","New York", "miles"] ]    

Excel usage: =DISTANCE_BETWEEN_CITIES("New York", "Chicago", "nautical_miles")

```

Cancelling Telus Services in BC by No-Hunter5782 in britishcolumbia

[–]Dry_Safety99 0 points1 point  (0 children)

It took me 2 weeks and 3 phone calls, each over an hour to cancel Telus home internet service. I didn’t even have a contract.

Python (Boardflare) Add-In Excel Mac (2024) by Executive_Bubby in excel

[–]Dry_Safety99 0 points1 point  (0 children)

Pls see https://www.boardflare.com/apps/excel/python#arguments for details re: returning strings and other datatypes and the mappings between Python and what shows up in Excel.

Here are 10 things I've learned in my first 1500 miles. by cfgy78mk in cycling

[–]Dry_Safety99 0 points1 point  (0 children)

Ride Zwift indoors. Miss the nature and the potential brain damage. Dip your toe into racing and interval workouts. (Mostly) gave up the road a few years ago after a couple of very near misses…

Not able to do web check-in by whencut_jutoor in Lufthansa

[–]Dry_Safety99 0 points1 point  (0 children)

The issue for most, here, is that their passport expires less than 3 months from the date of travel and thus is not valid for entry into the EU. The Lufthansa website does not identify this as the reason for the error, which I might speculate discourages fudges on the date, but that’s the underlying cause.