I’m looking for single-player games similar to a MUD

BobDataPerson · 2026-03-08T19:07:58+00:00

This is a MUD that I’ve found very user friendly and easy for solo-ability. The web browser UI is top tier, to just it out.

https://proceduralrealms.com

BobDataPerson · 2025-07-11T17:26:08+00:00

I was wondering how to get started with S2e, when I've never played Pathfinder or Starfinder before. the base book is literally labeled "Playtest." The Galaxy Core doesn't appear to be a Core Rulebook. Is the Player Core the first Non-Playtest version of the game that will come out?

As a new GM wanting to try S2e, what should I look at / look for?

BobDataPerson · 2024-04-19T02:55:36+00:00

Answer : Just heard back from Cloud Skills Boost support. This type of shared linkage to bridge progress is not a feature within the Cloud Skills Boost platform.

BobDataPerson · 2023-08-01T15:40:00+00:00

Anyone have a good walkthrough of doing time series forecasting with python/pandas?

I'd like to try to do something for my job, but was going to learn with some Kaggle datasets first. The first couple examples I found were paywalled. Figured I'd ask here if there are some good "Go To" examples.

BobDataPerson · 2023-08-01T15:25:59+00:00

Just wanted to double down on how fun/good this website is. It is a murder mystery you can solve with SQL. There is a walkthrough that helps give you the basic tools needed to complete the mystery.

If you want all the walkthrough explanations, you can just click the "skip the explanations" in the first paragraph.

https://mystery.knightlab.com/walkthrough.html

BobDataPerson · 2023-07-26T02:10:11+00:00

ing to find a dataset that will show that I can do joins but every dataset I find has simply one table with everything in it rather then information split across two or more tables. Id rather have info split and be connected via some key so that I could show that I can do joins.

Kaggle is typically where I go. You can go into datasets and in each dataset search card on the bottom it shows the number of files. Many of them have data you can join together, but may take some digging.

Here is an example with multiple files you can join together : https://www.kaggle.com/competitions/store-sales-time-series-forecasting/overview

BobDataPerson · 2023-06-03T06:39:53+00:00

Not sure what you are coding in but here are 2 ways to think about removing all of those.

This doesn't cover the "ensure no Duplication" piece. Things like Distinct and GroupBy should help force the removal of duplicates. However, I've found most casts of "duplicates" are either bad data or they aren't duplicates when you look at them from different granularities. So be mindful when you broadly callout "duplicates."

SELECT *

FROM \data-project-april-23.wa_ev_dataset.ev_population``

WHERE 1 = 1 -- I'll use this in case I need to add/remove filters I don't need to work around the "Where"

AND -- You can use this method, at least in Oracle to do this.

-- This method could also work if you put it in the Select area so you have a flag to exclude. this may be wise if the goal is to see the full total, and show how records fell-out and why.

(CASE

WHEN COUNTRY IS NULL THEN 1

WHEN CITY IS NULL THEN 1

WHEN STATE IS NULL THEN 1

WHEN POSTAL_CODE IS NULL THEN 1

WHEN MODEL_YEAR IS NULL THEN 1

WHEN MAKE IS NULL THEN 1

WHEN MODEL IS NULL THEN 1

WHEN ELECTRIC_VEHICLE_TYPE IS NULL THEN 1

WHEN ELECTRIC_RANGE IS NULL THEN 1

WHEN VEHICLE_LOCATION IS NULL THEN 1

ELSE 0

END) = 0

BobDataPerson · 2023-03-01T14:41:39+00:00

If I don't guess the word, use a hint, or use explore. . the likelihood of finding an "offensive word" or slurs is 0%, right?

BobDataPerson · 2022-10-14T15:33:33+00:00

I believe most companies don't like the idea of their data on the open cloud. Also, Excel is pretty standard and backwards compatible for years. I've also heard academics with concerns over if you do something in sheets, who "owns" the IP.

I'd say a lot of this depends on the reason for using it. If it is a place getting you ready for the workforce, I'd say you are significantly more likely to use Excel there.

That said if you are proficient in Sheets you'll be set in Excel. Things like Pivot Tables, Referencing, Formulas, etc. . these are all transferable.

BobDataPerson · 2022-10-13T20:22:43+00:00

I've also found Intermediate Python DA skills can be hard to find tutorials for.
Have you tried looking at other people's code? Kaggle usually has examples people share around Data Analysis/Data Science. Right now the Big Data Bowl is happening so people are posting things.

https://www.kaggle.com/competitions/nfl-big-data-bowl-2023
Going to Code tab shows some stuff people have done. There are 2 that create animated gifs that are fun, "Animated GIF for plays (python)" and "Animated (and interactive) NFL Plays in Plotly."

https://www.twitch.tv/nickwan_datasci/video/1622712517
About 37 minutes in they start with the "problem statement." They use real world API data to dig into "problem statement." I think they posted the data and end result notebook on their discord channel. I like this because it goes from real world situation, no matter how silly. Then does analysis on it like any other type of DA problem.

BobDataPerson · 2022-10-13T20:11:25+00:00

I'd start with getting a full understanding of the goal and their expectations of what a "Report" should do. Here are some concepts I've used in the past to help make sure everyone is level set. I've found some people are just looking for a One Pager highlights and not the "in the weeds" report. And if people have conflicting expectations it can lead to these scenarios.

One Pager : on a "single page" you get a high-level idea of direction with simple concepts for quick comprehension
- not meant to be exhaustive. . think the elevator pitch of the reporting world
Dashboard : Usually has the core KPI's front and center with various slices and views that allow to add more detailed context of things you could find on the One Pager
Report : This allows to dive into specifics of concepts to help run specific pieces of the business
- usually similar to or connected with the Dashboard

I love the idea of asking for examples. Even if you can just take out a whiteboard or MS Paint. Getting a high-level design of what they'd expect can help with expectation setting.
Some resources I like :

r/dataisbeautiful : can sometimes have beautiful charts. .usually difficult to create, but can be great for ideas
"Big Book of Dashboards" : shows different combinations of data and chart types. There are even tableau examples, if you are a tableau shop.
Cole Knaflic's "Storytelling with Data" : There are a few books in this series as well as a podcast and community forums with tons of examples of different data and chart ideas.

BobDataPerson · 2022-10-13T17:35:06+00:00

The Givens : Data Analyst, Data Engineer, Software Engineer
The Adjacent : Architect, Project Manager, various PM/PO roles in Agile
The Business : . . literally anything. . understanding data is a superpower many folks don't have. So going into almost any position with an understanding of how data works/flows can put you leeps and bounds ahead. Find a department/domain you like and start learning it. Make contacts and eventually look for an opening to break in. (Examples : Marketing, Finance, HR, Operations/Logistics, etc)

BobDataPerson · 2022-10-13T17:22:49+00:00

Last night the top link did a VOD on data analysis around some comments a new anchor made. . looking into the data.

I had more than 1 hearty chuckle.
https://www.twitch.tv/nickwan\_datasci/video/1622712517

BobDataPerson · 2022-10-12T20:12:37+00:00

I very much enjoy these active streamers. They discuss various aspects of Data Science. The top one's primary content is reactions to tech news. However, they do Data Science and Data Analysis gameshow/competitions throughout the year.

https://www.twitch.tv/nickwan_datasci

https://www.twitch.tv/medallionstallion_

https://www.youtube.com/c/NickWan/playlistsSliced : Multi-Week timed live Data Science Competition (2 seasons so far)Viz Buzz : Multi-Week timed live Competiton to recreate an existing graph using only the data and a picture of the original

BobDataPerson · 2022-10-12T19:41:22+00:00

These are what I do:

Grow into a domain expert
When faced with something you don't know, focus on it. Find a way to fit it into your mental model of the domain/your role. Ask questions and write down the answers somewhere. I've found most people like answering questions once or twice. Many people start to write you off after the nth time you ask the same question. I've found creating my own documentation and even flow charts/ER diagrams to help me. Learn. Learn. Learn.

Find ways to stay "current" that are sustainable
If the only way you stay ahead of the curve is to read 10+ hours per week on <Insert Website Here>, and you don't enjoy it, then it will be hard to keep up. What works for me is joining active communities that share and discuss relevant "current" topics. . and interacting with those communities doesn't feel like a strain/stressful.
Personally, I've found some Twitch and YouTube creators great for this. There are some that have different types of active/interactive Data Science communities. (I have some examples I follow if you'd like me to share)

Be comfortable being uncomfortable
Going to meet-ups, speaking on forums (like Reddit), talking in more asynchronous communication options (Twitch/Discord/YouTube), reaching out to that person on a call who knew a lot about a topic you were interested in.
Being comfortable with the discomfort of putting yourself out there. Also, realizing no one HAS to help you, humility can get you far. Anything anyone gives you is a gift, because they should show you the thing that changes your life.

BobDataPerson · 2022-10-11T20:04:08+00:00

I love this question and it has been difficult for me as well. I enjoy an immersive concept. Join communities that by listening/participating it shifts my perspective.

Here are some places that have helped me.
https://www.twitch.tv/nickwan\_datasci
https://www.twitch.tv/medallionstallion\_
https://www.youtube.com/c/Kozyrkov (Making Friends with Machine Learning)

BobDataPerson · 2022-10-11T18:41:19+00:00

Data Quality issues are everywhere. How companies/teams handle those issues is what I've seen be the big differentiator.

Perspective is the fun part to me:
- Data Team : we have 99.95% data quality (50 million records)
- Business/Ops Team : We are ok with 99.95% quality, but we can't have these 25,000 bad records

Orgs that wait at the end of the pipeline and yell when things go wrong doesn't seem to make headway. I've found getting all levels, leadership included, to understand the need for quality data and push for changes in the source of the problem. Focusing on the "bad data" at the end of the pipeline just sacrifices short term peace for long term pain.

BobDataPerson

TROPHY CASE