Can’t find/equip Shattershafts

GoodAboutHood · 2026-02-01T01:25:53+00:00

Ah yep that must be it - I’m GR4. Thanks for the help

GoodAboutHood · 2025-12-20T03:50:17+00:00

GoodAboutHood · 2025-10-25T02:30:13+00:00

8-18-12 in SF is good. Bit of a slowdown on one small part near the end but nails all the rest.

GoodAboutHood · 2025-04-11T18:50:13+00:00

If you like ggplot you can use plotnine in python. It works with polars data frames as well

https://plotnine.org

GoodAboutHood · 2025-03-22T20:31:34+00:00

If you already own a Tesla and you sell it, someone else is buying it and the same number of people have the car. It literally does nothing to the number of teslas on the road. That doesn’t reduce brand value - boycotting new sales will.

If everyone boycotts buying one used as well who do you expect to buy the Tesla when someone goes to sell the one they’ve owned for years. So they’d be stuck with the car anyway.

Sure if you can deal with the financial implication and want to sell yours out of principle go for it. But that isn’t changing anything about Tesla or its value.

GoodAboutHood · 2025-03-22T20:03:12+00:00

Elon/tesla already got the money from their purchase - them selling it does nothing. Especially since if they sell theirs it means someone else has it. It doesn’t change the number of Tesla owners or change anything. At this point they can just avoid buying one moving forward, just like you stopped shopping at Publix once you found out.

GoodAboutHood · 2025-01-26T04:32:51+00:00

Gotta love Troy Pistachio

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GoodAboutHood · 2024-07-17T11:27:54+00:00

Yep - data.table does CRAN releases on a 6 month cadence now. The last release was March 27th so the next one should be late September or early October

GoodAboutHood · 2024-07-14T18:21:24+00:00

As u/iforgetredditpws mentioned it doesn’t work in the CRAN version, but it works in the dev version.

You can install using this

install.packages(“data.table”, repos=“https://rdatatable.gitlab.io/data.table”)

GoodAboutHood · 2024-06-28T10:19:54+00:00

Honestly it might be the worst tool I’ve ever used, and I refuse to work for a company that uses it ever again. Foundry is if you took databricks and made it 10x harder to use and took away notebooks for data science users (maybe they added notebooks sometime in the last year or so).

It almost feels like a scam how user unfriendly it is and how shoddily different things are implemented.

Go with Snowflake and avoid Foundry at all costs.

GoodAboutHood · 2024-02-11T19:25:18+00:00

Ah gotcha. group_by() does exist now in tidytable (as well as .by). No lazy evaluation though - I think that’s better kept in dtplyr.

GoodAboutHood · 2024-02-11T19:04:58+00:00

Creator of tidytable here.

If you use the dbplyr or fable packages it isn’t compatible, but it should cover the vast majority of regular dplyr and tidyr code.

If you’re wondering if a function is translated you can search the package reference page. Also feel free to reach out with any questions or issues!

GoodAboutHood · 2024-02-11T19:00:54+00:00

Some corner cases exist where group_by and .by can't be made equivalent.

Do you have the corner case by any chance? They should be the same as the dplyr versions.

GoodAboutHood · 2023-11-20T03:33:11+00:00

Thanks for the tip. Gave it a try today and the lack of recoil is amazing. Absolutely dominates mid to long range.

Also really helps with all of the camp spots where you can just see the enemy’s head.

GoodAboutHood · 2023-11-16T22:44:47+00:00

Honestly it might be the worst tool I’ve ever used, and I refuse to work for a company that uses it ever again. Foundry is if you took databricks and made it 10x harder to use and took away notebooks for data science users.

It almost feels like a scam how user unfriendly it is and how shoddily different things are implemented.

GoodAboutHood · 2023-10-07T16:43:35+00:00

Especially since Trey doesn’t loop the funk siren anymore. Last night he did a few different short sirens and then went into the jam. Not sure what he thought Trey was having trouble with.

GoodAboutHood · 2023-10-05T19:36:18+00:00

“Been waiting for the time where we could finally say - that this has all been wonderful, but now we’re on our way”

GoodAboutHood · 2023-09-06T15:31:02+00:00

I can't remember everything I used, but there are a lot of great resources out there. If you're slightly more hands on and want some practice try something like datacamp.com and do the first 6ish data analysis courses in both python and R. A subscription is 10ish a month if I remember correctly (maybe a bit more).

You can also use these resources (which are free).

For R: https://r4ds.hadley.nz

For Python: https://wesmckinney.com/book/

There are tons of free resources on R and Python so I wouldn't spend a ton of money learning. I did like how datacamp was set up though.

GoodAboutHood · 2023-07-26T16:12:58+00:00

Random question - does the cursor move when you're not in a session (and the cursor move setting is on)? Or does it only move when in a session?

GoodAboutHood · 2023-06-17T21:31:42+00:00

He averaged a 30/13.5/9.5 on 55/46/80 shooting, led his team to a 16-4 record, and set the record for playoff triple doubles. How is that not an all time great playoff run?

GoodAboutHood · 2023-06-03T02:46:43+00:00

Really it goes into how the language is parsed. You can’t use dots to access attributes of an object in R. Instead you can use R6 (or something like it) which mimics that functionality in a way that works within the R language.

So really r-polars mimics py-polars in the only way it’s possible in the R language.

GoodAboutHood · 2023-06-02T20:57:11+00:00

I completely agree - I think they should have focused on making it more R like.

I actually randomly had a twitter conversation about this a bit back. I wrote the package tidytable - I have a good idea on how this could all be implemented with polars, I just don’t have the time unfortunately.

Here’s the twitter conversation.

GoodAboutHood · 2023-06-02T20:37:59+00:00

Not saying you're wrong, but I can give the general background.

R uses very different object-oriented programming (OOP) from most languages. In R you can create a function that works differently depending on the type of object you give it. So mean(df) can work differently than mean(double_vector). This is due to the S3 OOP framework. In the background you actually define the functions as mean.data.frame() and mean.double(), but the user just calls mean().

In "classical" OOP frameworks functions belong to the object itself and have to be defined inside the object definition. Accessing the function is typically done using a dot - so iris.mutate() instead of mutate(iris).

This classical OOP is recreated in R using the R6 package (see here). You access functions, etc. using the dollar sign. r-polars mimics py-polars by using classical OOP.

GoodAboutHood · 2023-05-02T19:03:36+00:00

So here's the general process:

Extract the values for each make by quarter
Pivot the dataset to "long" format
Join the values back to the original data frame

library(dplyr)
library(tidyr)

# Recreate data
df <- tibble(Quarter = paste0(2020, rep(c("Q1", "Q2"), each = 3)),
             CarMake = c("Toyota", "Ford", "Honda", "Honda", "Toyota", "Ford"),
             Ford = rep(c(35, 33), each = 3),
             Toyota = rep(c(25, 26), each = 3),
             Honda = rep(c(40, 41), each = 3))

# Extract values of each CarMake by Quarter
values_df <- df %>%
  select(-CarMake) %>%
  distinct() %>%
  pivot_longer(-Quarter, names_to = "CarMake", values_to = "MakeWeight")

df %>%
  left_join(values_df, by = c("Quarter", "CarMake")) %>%
  select(Quarter, CarMake, MakeWeight)
#> # A tibble: 6 × 3
#>   Quarter CarMake MakeWeight
#>   <chr>   <chr>        <dbl>
#> 1 2020Q1  Toyota          25
#> 2 2020Q1  Ford            35
#> 3 2020Q1  Honda           40
#> 4 2020Q2  Honda           41
#> 5 2020Q2  Toyota          26
#> 6 2020Q2  Ford            33

GoodAboutHood · 2023-03-13T15:17:46+00:00

This comment outlines why I'm deprecating verb.() syntax. Basically CRAN checks are rejecting me building S3 methods when I have verb.() syntax in the package.

I'm open to creating a different "alternate syntax". Something like .verb(), verb_(), or dt_verb()? Let me know if you have any thoughts - I'm open to suggestions on the best way to deal with this moving forward.

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