#sub2

[fapper]

I JUST WANT A MID SHYT TO MAKE OUT WITH AT THE FUCJING CLUBBB IS THAT TOO FAWKING MUCH TO ASK FOR OH NY GODDDDD not sub2 OLD ASS 40 YEAR OLDS GTFOOO😭😭😭😭🙏🙏🙏🙏 im on my KNEES WHERE ARE THE MEN IN THEIR MID 20S YALLL

[itsclydebitches]

SUBNAUTICA 2 TRAILER CLYDE

I KNOW I SAW!!!!!!!!! Just casually browsing my feed when that lovely alert popped up~

In all seriousness, that teaser makes me really hopeful/hyped for Sub2. I never joined the hate bandwagon for Below Zero, but I found it to just be a solid game, not one that re-captured the magic of the original. This though? This feels like og Subnautica. Even with the arrival of a friend (which might just be a nod to the promised co-op?), the whole teaser has that isolated, alienated feel to it. The world is gorgeous, but every beautiful thing posses a hidden danger. You are just a spec in the deep, dark, terrifying hole that is a foreign ocean. You're alone. The only voice for miles around is the semi-cold AI system trying to keep you alive. You're vulnerable.

There are just so many details here for a minute of info. The loud sound of your breathing. The blinking red alert light. The increasingly frantic beeping. The soft edges as your groggy brain remembers the pretty, safe surface. The fact that the crab-thing appears harmless but can still kill you with its presence alone. The "Oh shit if all the fish are swimming away there's something COMING" callback. The relief of seeing a friend show up before they're snatched by a GIANT BIO-LUMINESCENT CREATURE THAT'S JUST PERSUING ITS NATURAL INSTINCTS BUT ALSO IT'S NATURAL INSTINCTS ARE TERRIFYING." Perfect for spooky season.

(Although I'm ngl, my first thought was that Purple Dude might secretly be a friend like the Emperor Leviathan. It would fit the other parallels of that ending :D)

So yeah I'm PUMPED. Haven't been this excited for a sequel since Hades II, which admittedly hadn't been that long since EA released but STILL. I do have to decide though if I'm going to experience Sub2's EA. A part of me really wants to because a) I missed the initial EA experience and b) I'm impatient, but on the other hand the Subnautica series doesn't lend itself to incomplete play like a rogue-like does and I suspect it will be a lot more bug ridden than Hades II was when it came out... but we'll see. I'll probably join EA if only to avoid spoilers lol

[creations-of-the-dreamlight]

OMFG DO YOU THINK SUBNAUTICA THREE WILL BE US GOING BSCK TO CURE THE KARAA ON ITS SOURCE PLANET??

I still haven’t finish sub2 (ik) so maybe I’m forgetting some shit but if I remember correctly didn’t the architects bring the karaa from another planet to their home planet? And the testing to cure it was done on 4546B?

And the lore kind of solves all the loose ends for 4546b and the architects planet so where else do we have to go in this story then the very start of the Karaa? Plus I feel like a lot of people are speculating that karaa is going to be used by Alterra soooo… this is my theories but once again I am stoned and haven’t seen/done a proper play through since sub2 was pre-release.

[jams-sims]

The way I need the new character in Sub2 to be connected to the below zero. Listen give me weird ailen child from below zero. Since it seems like instead of "oh update your machine" it more "update yourself evolution 2".

Its not gonna happen but im actually super excited for subnatica 2!

[the-rookies-playbook]

I love to see a Women Win

(Amanda Nunes)

September 19, 2024 Rookie's Playbook

I’m back at it again deep diving into things I have no concept of, and today it’s the world of the UFC!  I like for my first read-through something to be an explanation of sorts so I can try and figure out exactly what is happening, and today I'm diving into the beauty of women champions. 

From my understanding there are four types of championships, there is feather-weight, bantam-weight, fly-weight, and straw-weight.  I’m not gonna lie, half of these to me sound like the same thing with AI generated names.  After doing further research it all depends on the weight of the fighter, which when I was younger used to confuse the hell out of me because I thought it was so rude to segregate people into weight categories, now however I know it’s so you don’t get absolutely murdered. 

Feather-weight(126 pounds) has no current champion, but they do have three past champions.  Amanda Nunes won in 2018 with two defenses and a TKO of 1 over her opponent Cris Cyborg.  I’m not going to sit here and lie to you either if my last name was Cyborg no one could talk to me. That is such badass.  The only knowledge I have of a TKO(Total Knockout) is when executed the fighter is left unable to complete the fight, so that is insanely hardcore to me.  Currently, the brazilian fighter has insane stats ranging from 13-2 TKO, SUB 4-2, and W-L-D 23-5-0.  Now, again I will not lie to you I only know what the TKO is.  

Sub is when a fighter ‘taps out’, yielding to their opponent so that they win.  So, that takes the badass levels down some, but hey who knows this could actually be the lowest for someone and she is the dominant woman to have ever lived.  Then the W-L-D is win, loss, or draw.  The thing that I'm getting at for Nunes is that she doesn’t believe in draws and eats up her opponent every time, 23 wins! Insane! 

Now that I know the terms let's move onto bantamweight, which is the 135 pound limit.  The current champion for this category is Raquel Pennington, with an outcome of a UD over Mayra Bueno Silva.  Now comes my next question, the hell is a UD? This is a term I have heard of and often yell out when I want to look knowledgeable, it means unanimous decision.  This is when all the judges are in agreement of which fighter is the winner, so good for Miss Pennington! 

Pennington’s stats are W-L-D 16-9-0, TKO 1-1, and sub is 1-1, not bad but not my new favorite fighter Amanda Nunes good.

Women’s flyweight is next on our list and their poundage (?) is 125.  I’m going to be honest, with all the searching and rules about the fighters weight is insane to me, what is a one pound difference in the grand scheme of it all you know? Anyway, the current champion of this category is Valentina Shevchenko who won in a unanimous decision against Alexas Grasso! Look at me knowing my terms, this is what we call development guys.   Shevchenko’s stats are W-L-D 24-4-1, TKO 8-1, and Sub 7-1.  I’m gonna be honest, Miss Nunes has my heart, but Schevchenko scares the shit outta me the most. 

The final category is straw-weight and the weight is 115 pounds, again the names just all seem too similar for my taste and I find them very much confusing but non the less I digress.  The current champion is the lady with the best cheekbones I have ever seen Zhang Weili who won against Carla Esparza with a Sub2.  Her stats rival Nunes to me with a W-L-D 25-3-0, TKO 11-1, and Sub 8-0.  She is a Chinese fighter whose career I feel I will be following closely. 

After all that research I can confirm that this is the most intriguing of the sports I have covered so far, and I simply cannot wait to learn more about it.

[penny-anna]

okay sub legacy thoughts w spoilers (by 'spoilers' i mean comments on changes made from the OG not plot spoilers) (i am a little way into the lab)

keeping the coin but moving the code to get the fuse elsewhere? DICK move. took me ages to find it. not sure if it's randomised but if it is then i think i got unlucky with the second 2 digits being 11 bcos it wasn't actually obvious that they were numbers when i found them

oughhhhh took me till sub2 to recognise the dimensional co-ordinates i was running into that's really neat and im so hype to see where we're going with that

where is the spoon and the fork... where is my classic submachine cutlery puzzle :(

i appreciate that there's more explanation for what you're doing w the chemicals in the lab (that's always been a bit of a ?? puzzle as it seems to hinge on knowledge that the player doesn't actually have so you're basically just combining items till you hit on the right combo). however i always liked the detail that you're straight up breaking in rather than hunting around for the code for entry so i wish that had been kept!!

!!!!! when re-opening the game and spotting sub 0 added to the level map

ok i need to stop now bcos it's late and also im supposed to be reducing screen time bcos of my eyes. off to bed shortly zzz good night.

[locoier]

i remember like. literally two years ago talking to someone about how sub2:30 seemed almost impossible for AA and now fein has a sub2:15. that is fucking insane but also if anyone could do it it would be feinberg.

[raedas]

it is a good day bc i got a sub2 time in set yayyyyyyy

[mwseo]

TWIN PEAKS

s01 - sUB

02 - sUB1 / sUB2

Fuego Camina Conmigo (1992)

03 - sUB

[fuckyeahreligionpigeon]

This is an example of religious rules/laws made humorous.

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[fapper]

This is abt to be me but with a sub2 white guy with glasses

[stopsmoking666]

Making Data Management Decisions

Source Code:

import pandas

import numpy

# any additional libraries would be imported here

data = pandas.read_csv('nesarc_pds.csv', low_memory=False)

# bug fix for display formats to avoid run time errors

pandas.set_option('display.float_format', lambda x:'%f'%x)

#setting variables you will be working with to numeric (updated)

#removal of BLANKS to avoid recoding failure in the next step

data['S1Q2F']=data['S1Q2F'].replace(" ", numpy.nan)

data['S1Q2D']=data['S1Q2D'].replace(" ", numpy.nan)

data['S1Q2F'] = pandas.to_numeric(data['S1Q2F'])

data['S1Q2D'] = pandas.to_numeric(data['S1Q2D'])

data['AGE'] = pandas.to_numeric(data['AGE'])

#subset data to young adults age 18 to 25 who have smoked in the past 12 months

sub1=data[(data['AGE']>=17) & (data['AGE']<=34)]

#make a copy of my new subsetted data

sub2 = sub1.copy()

print ("_____________________________________________________________________")

print ('Counts for original S1Q2F')

c1 = sub2['S1Q2F'].value_counts(sort=False, dropna=False)

print(c1)

print ("_____________________________________________________________________")

# recode missing values to python missing (NaN)

sub2['S1Q2F']=sub2['S1Q2F'].replace(9, numpy.nan)

#Showing all data with 9=Unknown set to NaN

print ('Counts for S1Q2F with 9 set to NAN and number of missing requested')

c2 = sub2['S1Q2F'].value_counts(sort=True, dropna=False)

print(c2)

print ("_____________________________________________________________________")

#Hiding the NaN data entries

print ('Counts for S1Q2F with 9 set to NAN and hiding of missing requested')

c2 = sub2['S1Q2F'].value_counts(sort=True, dropna= True)

print(c2)

print ("_____________________________________________________________________")

#AGE quartiles grouping into 4

print ('AGE - 4 categories - quartiles')

sub2['AGEGROUP1']=pandas.qcut(sub2.AGE, 4, labels=["1=0%tile","2=25%tile","3=50%tile","4=75%tile"])

c3 = sub2['AGEGROUP1'].value_counts(sort=False, dropna=True)

print(c3)

# recode missing values to python missing (NaN)

sub2['S1Q2D']=sub2['S1Q2D'].replace(9, numpy.nan)

#Showing all data with 9=Unknown set to NaN

print ('Counts for S1Q2D with 9 set to NAN and number of missing requested')

c4 = sub2['S1Q2D'].value_counts(sort=True, dropna= True)

print(c4)

print ("_____________________________________________________________________")

Result:

Counts for original S1Q2F S1Q2F NaN 10629 1.000000 2429 2.000000 570 4.000000 70 3.000000 119 9.000000 2 Name: count, dtype: int64

The result is showing the familiy situation of the selected AGE group between 18 and 35. All aswers are included.

Counts for S1Q2F with 9 set to NAN and number of missing requested S1Q2F NaN 10631 1.000000 2429 2.000000 570 3.000000 119 4.000000 70 Name: count, dtype: int64

The result is showing the familiy situation of the selected AGE group between 18 and 35. All aswers for unknown are included as NaN

Counts for S1Q2F with 9 set to NAN and hiding of missing requested S1Q2F 1.000000 2429 2.000000 570 3.000000 119 4.000000 70 Name: count, dtype: int64

The result is showing the familiy situation of the selected AGE group between 18 and 35. All aswers for unknown are included as NaN but have been removed from the output for more clarity of the data.

AGE - 4 categories - quartiles AGEGROUP1 1=0%tile 3665 2=25%tile 3503 3=50%tile 3228 4=75%tile 3423 Name: count, dtype: int64

The result is showing the percentiles of the AGE grouped into 4 categories

Counts for S1Q2D with 9 set to NAN and number of missing requested S1Q2D 2.000000 7659 1.000000 3021 Name: count, dtype: int64

The result is showing the if the familiy got divorced (1=yes, 2=No) of the selected AGE group between 18 and 35. All aswers for unknown are included as NaN but have been removed from the output for more clarity of the data

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[abhinav3045]

Creating a graphs for your data

CODE

#Univariate bar graph for categorical variables sub2["S2DQ1"] = sub2["S2DQ1"].astype('category') seaborn.countplot(x="S2DQ1", data=sub2) plt.xlabel('Father´s problems with liquor') plt.title('Father´s problems with liquor in young people between 17 and 28 years old who spend a lot of time drinking (NESARC Study)')

sub2["S2DQ2"] = sub2["S2DQ2"].astype('category')

seaborn.countplot(x="S2DQ2", data=sub2) plt.xlabel('Mother´s problems with liquor') plt.title('Mother´s problems with liquor in young people between 17 and 28 years old who spend a lot of time drinking (NESARC Study)') #Univariate histogram for quantitative variable: seaborn.distplot(sub2["S2BQ2D"].dropna(), kde=False); plt.xlabel('Age of onset of liquor dependence') plt.title('Age of onset of liquor dependence in young people between 17 and 28 years old who spend a lot of time drinking (NESARC Study)') sub2['S2BQ2D'] = pandas.cut(sub2.S2BQ2D, [7, 13, 17, 20, 23, 27]) c5 = sub2['S2BQ2D'].value_counts(sort=False, dropna=True) print(c5) sub2['S2BQ2D'] = sub2['S2BQ2D'].astype('category')

sub2['S2DQ1'] = pandas.to_numeric(sub2['S2DQ1']==1) seaborn.catplot(x="S2BQ2D", y="S2DQ1", data=sub2, kind="bar", ci=None) plt.xlabel('Age of onset of liquor dependence') plt.ylabel('Proportion father´s problems with liquor') sub2['S2DQ2'] = pandas.to_numeric(sub2['S2DQ2']==1) seaborn.catplot(x="S2BQ2D", y="S2DQ2", data=sub2, kind="bar", ci=None) plt.xlabel('Age of onset of liquor dependence') plt.ylabel('Proportion father´s problems with liquor')

OUTPUT

DESCRIPTION

Regarding the graphs of the quantitative variable that represents the age of onset of liquor dependence, it has a symmetrical unimodal distribution where the mode, mean and median are approximately 18 years of age. Regarding the categorical variables, 337 young people stated that their father had problems with liquor and 141 stated that their mother suffered from alcoholism. I made two bivariate graphs taking as an explanatory variable the age of onset of alcohol dependence and comparing it with the proportion of fathers and mothers who had problems with alcohol. In the case of the father, the data follow a bimodal distribution where the modes are found at ages 7-13 and 23-27. On the other hand, the graph where the mother's condition is represented shows a skewed right unimodal behavior. In conclusion, it can be observed that both mothers and fathers who suffered from alcoholism influenced their children mainly at early ages (7 -13) had problems with liquor. For future analyses, the influence that other family members such as grandparents, uncles, or romantic partners have on alcohol consumption could be taken into account.

[bilvensstuff]

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