What we should get.
This is a translation of a post from 2020
This is a step-by-step guide to generating dungeons in Python. If you are not a programmer, you may be interested in reading how to design a dungeon [ru].
I spent a few evenings testing the idea of generating space bases.. The space base didn't work out, but the result looks like a good dungeon. Since I went from simple to complex and didn't use rocket science, I converted the code into a tutorial on generating dungeons in Python.
By the end of this tutorial, we will have a dungeon generator with the following features:
The entire code can be found on github.
There won't be any code in the post — all the approaches used can be easily described in words. At least, I think so.
Each development stage has a corresponding tag in the repository, containing the code at the end of the stage.
The aim of this tutorial is not only to teach how to generate dungeons but to demonstrate that seemingly complex tasks can be simple when properly broken down into subtasks.
Looking at the survey data and trying to find something useful.
Recently I've conducted a survey about the preferences of strategy players.
In the previous post, we cleaned up the data, and in this one, we will try to find insights within it.
In this post you will find an interactive dashboard with a bunch of charts, where you can compare two samples of your choice. There are many samples — for every taste and color, so feel free to explore and share the patterns you find on Telegram and Discord.
But be careful with conclusions. There is little data, in some cases very little. For example, the difference between the sample sizes of male and female respondents is about tenfold => you should be very careful in interpreting the differences between them.
In general, do not take this post as a full-fledged study. I'm sure many analysts would have torn my hands off for such a thing. Then sewed them back and torn them off again :-D Use the post as an interface to the data, and make your own conclusions.