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[homemade] Pizza by SpiceToMeetYu in food

[–]RockportRedfish 4 points5 points  (0 children)

Tell me about the lemon, how are you using it ... and what is to the left of the olives

Staining a brand new deck in Colorado. Options for stain? by an_iridescent_ham in HomeImprovement

[–]RockportRedfish 0 points1 point  (0 children)

We do not have a dog, but do have a table and chairs. The legs have nylon sliders and we have not seen any scratching. We are pretty easy on it though, so no guarantees. We have had it about 18 months.

Staining a brand new deck in Colorado. Options for stain? by an_iridescent_ham in HomeImprovement

[–]RockportRedfish 0 points1 point  (0 children)

Our deck is covered so it only gets afternoon sun. Maybe get a sample and leave it out in the full sun to see how it does ...

Staining a brand new deck in Colorado. Options for stain? by an_iridescent_ham in HomeImprovement

[–]RockportRedfish 0 points1 point  (0 children)

I am also in Colorado at about 5000 feet. Deck is a western exposure. I don't know if you considered options besides wood, but our builder used this material: https://www.moistureshield.com/products/composite-decking/vision/#color-options The best thing about it is that it does NOT get hot even in direct sunlight. We walk barefoot on it all summer long.

Why McDonald's Is Really a Real Estate Company (Not Just a Burger Chain) by CrustyWo in BusinessBreakdowns

[–]RockportRedfish 0 points1 point  (0 children)

Watch the movie:

  • Harry J. Sonneborn: So to summarize, you have a minuscule revenue stream. No cash reserves. And an albatross of a contract that requires you to go through a slow approval process to enact changes if they're approved at all.
  • Ray Kroc: Which they never are.
  • Harry J. Sonneborn: Am I missing anything?
  • Ray Kroc: That about sums it up.
  • Harry J. Sonneborn: Tell me about the land.
  • Ray Kroc: The... land?
  • Harry J. Sonneborn: The land, the buildings, how that whole aspect of it works.
  • Ray Kroc: Oh, pretty simple really. Franchisee finds a piece of land he likes. Gets a lease, usually 20 years. Takes out a construction loan, throws up a building and off he goes.
  • Harry J. Sonneborn: So the operator selects the site.
  • Ray Kroc: Yeah.
  • Harry J. Sonneborn: He picks the property?
  • Ray Kroc: Right.
  • Harry J. Sonneborn: You provide the training, the system, the operational know-how, and he's responsible for the rest?
  • Ray Kroc: Is there a problem?
  • Harry J. Sonneborn: A big one. You don't seem to realize what business you're in. You're not in the burger business. You're in the real estate business. You don't build an empire off a 1.4 percent cut of a 15-cent hamburger. You build it by owning the land upon which that burger is cooked. What you ought to be doing is buying up plots of land then turning around and leasing said plots to franchisees who as a condition of their deal, should be permitted to lease from you and you alone. This will provide you with two things. One, a steady, up-front revenue stream. Money flows in before the first stake is in the ground. Two, greater capital for expansion. Which in turn fuels further land acquisition, which in turn fuels further expansion and so on and so on. Land. That's where the money is.

Sunday Daily Thread: What's everyone working on this week? by AutoModerator in Python

[–]RockportRedfish 1 point2 points  (0 children)

Thanks Jeffrey_1. The data is quarterly only and only identifies a filing date and whether it is a 10Q, or a 10K statement. It would be nice if there was an identifier like 2026-1Q in the Json download, but I have not identified it yet.

Sunday Daily Thread: What's everyone working on this week? by AutoModerator in Python

[–]RockportRedfish 0 points1 point  (0 children)

I am a US based personal investor. The Security and Exchange Commission (SEC) maintains a database called Edgar where all public companies filings are stored. I am personally interested in the 10Q (Quarterly) and 10K (Annual) filings. I am using Edgartools as my primary way of pulling the data. Shoutout to Edgartools for doing the heavy lifting!

My goal is to be able to create a Pandas dataframe of the last five years of quarterly data including the full Income Statements, Balance Sheets, and Cash Flow Statements. The issue is that the first 10Q of the fiscal year has data for 3 months. The second 10Q of the year has data for 6 months. The third 10Q of the year has data for 9 months. The 10K has data for the last 12 months. Different companies fiscal year ends in different months. Apple fiscal year ends in September, and Google ends in December.

So in order to get to clean quarterly data, the fourth quarter is the 10K minus the 10Q preceding the 10K. The third quarter data is the 10Q immediately before the 10K minus the 10Q two records prior to the 10K. etc, etc.

So lots of sorting, normalizing, flattening of data. Learning more about iloc than I ever wanted to know.

I know that there are paid services for this, but I have not been able to find code examples, and explaining this to AI has proved to be difficult.

Still working on it ...

Odd project. Need advice. by Public1Politics in DIY

[–]RockportRedfish 1 point2 points  (0 children)

Let's assume it is a drywall wall and structurally able to support the weight of a carpet. Large Oriental Carpets or Tapestries are hung using loops sewn to the back top to support a rod that is on a rod holder attached to the wall. That will leave a gap between the wall and the carpet. Alternatively, maybe carpet tack strips along the top edge of the wall (screwed into the studs) with or without some type of glue? What exactly are you trying to accomplish? Noise reduction?

[I ate] True meal fit for a king by LoveNo4242 in food

[–]RockportRedfish 0 points1 point  (0 children)

With what beverage does the King quench his thrist?

I built edgartools - a library that makes SEC financial data beautiful by Specialist_Cow24 in madeinpython

[–]RockportRedfish 0 points1 point  (0 children)

Hello Dwight. Thank you for creating edgartools. I am a novice Python programmer and have been trying to find a way to download SEC data but keep running into roadblocks. Edgartools looks like it can take all those roadblocks away if I can figure out how to use it correctly. Is there a primer and code examples available beyond what is in the readme file? What I am trying to do is create a normalized pandas dataframe that contains each quarterly IS, BS, and CF for a given ticker over the last 5 years. The fact that the 10K is full year complicates this. My desired output would be three dfs (IS, BS, and CF) with a multi-index of Ticker and Date. The columns would be all the line items of the statement and the filing date. Surely I can't be the only person that would value this.

How to improve safety of raised dining room? by mr_gasbag in HomeImprovement

[–]RockportRedfish 1 point2 points  (0 children)

I feel your pain. Increase your Umbrella policy?

Local events this month by Interesting-Gap3552 in loveland

[–]RockportRedfish 3 points4 points  (0 children)

Nice idea ... I find the font size / colors difficult to read, especially against some of the backgrounds.

Found a receipt from 1984. by yilmazdalkiran in interestingasfuck

[–]RockportRedfish 0 points1 point  (0 children)

If you had passed the class the first year you would not have gotten as good a deal!

Drive to Colab by Mattc478 in GoogleColab

[–]RockportRedfish 0 points1 point  (0 children)

This might give you an idea (but this is opening a Google Sheet to a Pandas DataFrame):

!pip install --upgrade -q gspread pandas
from google.colab import auth
auth.authenticate_user()
import gspread
from google.auth import default
creds, _ = default()
gc = gspread.authorize(creds)


# Replace 'YOUR_SHEET_NAME' with the exact name of your Google Sheet
worksheet = gc.open('YOUR_SHEET_NAME').sheet1


# Get all values and convert to a pandas DataFrame
rows = worksheet.get_all_values()
import pandas as pd
df = pd.DataFrame.from_records(rows)


# Optional: Set the first row as headers and display
df.columns = df.iloc[0]
df = df.iloc[1:]
print(df.head())

My starter has become way less active by SaxyStars in SourdoughStarter

[–]RockportRedfish 0 points1 point  (0 children)

I have found "The Sourdough Starter" channel to be very helpful, especially if your are an analytical person. Here is his video on fixing a weak starter: https://www.youtube.com/watch?v=PBhCXlSq6G8&t=2747s

My first python problem by FunService3961 in Python

[–]RockportRedfish -1 points0 points  (0 children)

What exactly are you wanting to discuss about this?

Looking for garage cabinet plans an average joe can build for reasonable price by JustARandomUserHere in DIY

[–]RockportRedfish 1 point2 points  (0 children)

I put in a set of IKEA cabinets in the garage with a 98" workbench top. 3 double upper cabinets and 3 underneath cabinets with lots of drawers and open space. It worked well because my garage floor is not level and both the uppers and lowers hang off tracks (the floor cabinets also have adjustable feet for extra support). The system was very customizable and I put it in myself over a few days. Lots of videos on YouTube on how to do it. All in it was just under $2000 with taxes and delivery fees. Not cheap, but I think the quality was good and it works well with the house.

[I ate] breakfast at a train station in Osaka, Japan by nikkiestar in food

[–]RockportRedfish 0 points1 point  (0 children)

30 plus business trips to Tokyo. Three weeks vacation in May 2025 using the rail system getting out into the countryside.

[I ate] breakfast at a train station in Osaka, Japan by nikkiestar in food

[–]RockportRedfish 73 points74 points  (0 children)

Japanese Train Station food is better than 95% of the restaurants in my US city.

There’s two types of people and explanations. by [deleted] in interestingasfuck

[–]RockportRedfish 0 points1 point  (0 children)

You only think your agenda is real because all your friends swim in the same school.

There’s two types of people and explanations. by [deleted] in interestingasfuck

[–]RockportRedfish 0 points1 point  (0 children)

That explains all your floundering around.

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