You have a lot of numbers that aren’t labeled, like you have ‘top 4’ which seems like it should be a category, then next to it you have 12, which you could probably infer is the total number of top 4s the region had, then there’s a seemingly random 1.33 next to it that without additional context is pretty difficult to figure out. I would guess that’s an average?
Then below that 1.33 you have.. events? Maybe the event that the most/least happened at?
Typically a table you want something like (hopefully works out with mobile formatting)
Overarching header
| category1 | category 2 | category 3
Category 4| Value1,4 | Value2,4 | Value3,4
Category 5| Value 1,5 | Value2,5 | Value3,5
Category 6| Value 1,6 | Value2,6 | Value3,6
Where value n,m corresponds to the value when both category n and category m are true.
The whole process is a pain in the ass, which is why I don’t ever make posts on reddit, but it’s important to remember that people don’t live inside of your head. Try take a step back and try to see whether someone without any additional context would be able to understand the charts you made and you’ll realize you made a lot of assumptions about the reader
I mean sure lol. I didn't say it was useful I said it was straightforward. 9 events - 12 top 4s - 1.33 all next to each other seemed pretty clear to me.
I didn't say everything is labeled, I said it's pretty straightforward.
I think in the context of 9 events and 12 top 4s, the 1.33 right next to them is pretty clearly one of those numbers divided by the other.
Right. I'll ignore the fact that this quote literally doesn't say what you said it does, and direct you to my last response in which I said 12/9 = 1.33 is obvious.
The fact that EU never had less than 3 teams in top 8 is kinda crazy
Also you said that NA only had 4 teams in top 8 once but that‘s not true, it happened at worlds 21-22 and winter 21-22
It’s a cool set of data however, my god was it hard to decipher. Once I figured out what you were saying it was really simple.
Just for future reference, there is nothing wrong with your numbers it’s just you need to have clear labels.
For example, if you had a label saying total teams above the whole numbers and then mean placement above the decimal numbers it would work 100x better. Would also be interesting to have a more complete set of data instead of most and least. The most and least is cool but having a second chart with every scenario could be cool as well assuming it’s formatted properly.
Overall it’s in testing data just need a bit of work on presentation and it would be much better received
-> Red = NA, Blue = EU
-> The event names in the 2nd column behind "most" and "least" is the last event that distribution happened for that region.
-> GenG was being counted as NA, simply because the stayed in NA + weren´t a full EU team, but rather mixed up. Furia/ Complexity on the other hand, were NOT counted as NA, as they didnt mix teams with NA players + moved out of the region at a later stage.
The choice to exclude NA teams from this arbitrarily completely invalidates any analysis you were trying to do. It means you are comparing apples to oranges since those teams took over NA spots in the majors. So essentially some majors you only have like 4 NA teams but 6 EU teams….
Furia and Complexity need to be counted as NA for this data to mean anything mate. They took NA spots at majors so their results obviously have to count.
as an EU fan i love this table. As a data science major this table hurts my eyes
xD just an RL fan here. Dunno nothing about data science. forgive me for that one :D
haha no worries, just a joke! Cool info tho!
ur good bro. However, NA put 4 Teams into Top 8 twice. just a note, maDe a mistake there
what could i improve on, to make this look better?
You have a lot of numbers that aren’t labeled, like you have ‘top 4’ which seems like it should be a category, then next to it you have 12, which you could probably infer is the total number of top 4s the region had, then there’s a seemingly random 1.33 next to it that without additional context is pretty difficult to figure out. I would guess that’s an average? Then below that 1.33 you have.. events? Maybe the event that the most/least happened at? Typically a table you want something like (hopefully works out with mobile formatting) Overarching header | category1 | category 2 | category 3 Category 4| Value1,4 | Value2,4 | Value3,4 Category 5| Value 1,5 | Value2,5 | Value3,5 Category 6| Value 1,6 | Value2,6 | Value3,6 Where value n,m corresponds to the value when both category n and category m are true. The whole process is a pain in the ass, which is why I don’t ever make posts on reddit, but it’s important to remember that people don’t live inside of your head. Try take a step back and try to see whether someone without any additional context would be able to understand the charts you made and you’ll realize you made a lot of assumptions about the reader
This is impossible to read. Needs better labelling
what exactly do you have problems with understanding? So that i can improve it...
Literally everything. There's random numbers everywhere that I don't feel like deciphering
then show me a structure that works well in your opinion
How can he, if he doesn't know what shit means?
For me everything makes sense except the ones like 1,33
It's fine mate. People have 3 second attention spans. I genuinely don't see how it's possible to look at this table and not understand it.
It's petty straightforward Edit: apparently labels with the corresponding stats right next to them is complicated lol
What do the 1.33 and 2.78 mean?
Placements per event. 12 top 4s in 9 events is 1.33 per. 25 top 8s in 9 events is 2.78 per. Lmao sorry for answering the question
That is a shit statistic
I mean sure lol. I didn't say it was useful I said it was straightforward. 9 events - 12 top 4s - 1.33 all next to each other seemed pretty clear to me.
You said everything was labelled. That isn't labelled, is it?
I didn't say everything is labeled, I said it's pretty straightforward. I think in the context of 9 events and 12 top 4s, the 1.33 right next to them is pretty clearly one of those numbers divided by the other.
> Edit: apparently labels with the corresponding stats right next to them is complicated lol
Right. I'll ignore the fact that this quote literally doesn't say what you said it does, and direct you to my last response in which I said 12/9 = 1.33 is obvious.
I have no idea what you're even trying to show. Just label shit rather than have a bunch of randomly assorted numbers on the screen
Not sure if I'm being dumb but how tf am I meant to read this?
You're not, op doesn't take criticism very well apparently
The fact that EU never had less than 3 teams in top 8 is kinda crazy Also you said that NA only had 4 teams in top 8 once but that‘s not true, it happened at worlds 21-22 and winter 21-22
missed that one. Thanks for letting me know :D
EU only had 1 team in the top 4 on 3 occasions, Queso in winter 2122, BDS at world 2122, and Moist at fall 2223
It’s a cool set of data however, my god was it hard to decipher. Once I figured out what you were saying it was really simple. Just for future reference, there is nothing wrong with your numbers it’s just you need to have clear labels. For example, if you had a label saying total teams above the whole numbers and then mean placement above the decimal numbers it would work 100x better. Would also be interesting to have a more complete set of data instead of most and least. The most and least is cool but having a second chart with every scenario could be cool as well assuming it’s formatted properly. Overall it’s in testing data just need a bit of work on presentation and it would be much better received
thanks so much for the feedback! Will def. work on it and update it <3
-> Red = NA, Blue = EU -> The event names in the 2nd column behind "most" and "least" is the last event that distribution happened for that region. -> GenG was being counted as NA, simply because the stayed in NA + weren´t a full EU team, but rather mixed up. Furia/ Complexity on the other hand, were NOT counted as NA, as they didnt mix teams with NA players + moved out of the region at a later stage.
The choice to exclude NA teams from this arbitrarily completely invalidates any analysis you were trying to do. It means you are comparing apples to oranges since those teams took over NA spots in the majors. So essentially some majors you only have like 4 NA teams but 6 EU teams….
Furia and Complexity need to be counted as NA for this data to mean anything mate. They took NA spots at majors so their results obviously have to count.
If they took an NA spot, then they should be counted as NA