#Episode 26.01

[dndadsepisodecovers]

Ep.26.01- Moms of Future Past

[bluerosesdiary]

movies & tv shows wrap-up - 2022

tv shows:

sex&drugs&rock&roll (2015-2016) s01 19.01 s02 05.02

jessica jones (2015-2019) s01 26.01 s02 24.10

snowdrop (2021) 31.01

dollface (2019-2022) s02 12.02

teen wolf (2011-2017) s01 13.02 s02 03.03 s03 12.04 s04 04.05 s05 10.06 s06 05.07

daredevil (2015-2018) s02 14.02

pam&tommy (2022) 10.03

luke cage (2016-2018) s01 15.03

normal people (2020) 24.03

scenes from a marriage (2021) 16.04

iron fist (2017-2018) s01 01.05

moon knight (2022) 04.05

clark (2022) 07.05

the defenders (2017) 23.05

under the banner of heaven (2022) 02.06

gossip girl (2007-2012) s01 03.06 s02 06.08 s03 01.09 s04 20.09 s05 08.11 s06 18.11

barry (2018-) s03 13.06

stranger things (2016-) s04vol1 16.06 s04vol2 02.07

first kill (2022) 21.06

ms marvel (2022) 13.07

resident evil (2022) 17.07

the mandalorian (2019-) s01 19.07 s02 03.08

winx club (2004-2019) s07 28.07

midnight mass (2021) 03.08

riverdale (2017-) s06 03.08

i am groot (2022) 10.08

the book of boba fett (2021-) 16.08

only murders in the building (2021-) s02 23.08

partner track (2022) 29.08

the punisher (2017-2019) s01 05.09

obi-wan kenobi (2022) 06.09

american horror stories (2021-) s02 08.09

the boys (2019-) s01 14.09 s02 27.09 s03 15.10

the sandman (2022-) 18.09

fate: the winx saga (2021-2022) s02 29.09

the midnight club (2022) 12.10

she-hulk: attorney at law (2022) 13.10

the order (2019-2020) s01 20.10

american horror story (2011-) s11 17.11

andor (2022) 24.11

scream: the tv series (2015-2019) s01 02.12

the sex lives of college girls (2021-) s02 15.12

supernatural (2005-2020) s01 18.12 s02 25.12 s03 30.12

treason (2022) 26.12

movies:

tick, tick...boom! (2021) 08.01

the 355 (2022) 11.01

eternals (2021) 12.01

carrie (2013) 13.01

hush (2016) 14.01

ghostbusters: afterlife (2021) 03.02

scream 2 (1997) 10.02

scream 3 (2000) 15.02

redeeming love (2022) 17.02

as above, so below (2014) 18.02

scream 4 (2011) 19.02

scream (2022) 24.02

fresh (2022) 02.03

the last full measure (2020) 06.03

the tale of two sisters (2003) 12.03

fantastic four (2005) 14.03

song for a raggy boy (2003) 15.03

4: rise of the silver surfer (2007) 25.03

obce niebo (2015) 28.03

the magdalene sisters (2002) 29.03

moonshot (2022) 31.03

i, tonya (2017) 02.04

uncharted (2022) 04.04

the covenant (2006) 09.04

metal lords (2022) 12.04

marrowbone (2017) 17.04

fantastic four (2015) 01.05

morbius (2022) 02.05

doctor strange in the multiverse of madness (2022) 11.05

little women (2019) 14.05

firestarter (2022) 21.05

fantastic beasts: the secrets of dumbledore (2022) 29.05

i'm not here (2017) 30.05

star wars: episode I - the phantom menace (1999) 23.06

lightyear (2022) 24.06

star wars: episode II - attack of the clones (2002) 24.06

star wars: episode III - revenge of the sith (2005) 25.06

star wars: episode IV - a new hope (1977) 26.06

american psycho (2000) 26.06

star wars: episode V - the empire strikes back (1980) 27.06

star wars: episode VI - return of the jedi (1983) 29.06

star wars: episode VII - the force awakens (2015) 30.06

star wars: episode VIII - the last jedi (2017) 03.07

star wars: episode IX - the rise of skywalker (2019) 07.07

rogue one: a star wars story (2016) 08.07

mamma mia! (2008) 09.07

mamma mia! here we go again (2018) 11.07

solo: a star wars story (2018) 12.07

the shining (1980) 18.07

the gray man (2022) 22.07

under the silver lake (2018) 23.07

not okay (2022) 29.07

my little pony: the movie (2017) 31.07

make up (2019) 07.08

thor: love and thunder (2022) 09.08

the maze runner (2014) 13.08

maze runner: the scorch trials (2015) 14.08

maze runner: the death cure (2018) 15.08

look both ways (2022) 17.08

doctor sleep (2019) 20.08

knives out (2019) 28.08

clueless (1995) 03.09

free guy (2021) 04.09

margaux (2022) 09.09

about fate (2022) 10.09

x (2022) 11.09

do revenge (2022) 16.09

carrie (1976) 19.09

der perfumeur (2022) 21.09

fear street (2021) 30.09

fear street 2 (2021) 01.10

fear street 3 (2021) 02.10

mr. harrigan's phone (2022) 05.10

werewolf by night (2022) 07.10

jane (2022) 21.10

luckiest girl alive (2022) 22.10

barbarian (2022) 25.10

sztuka kochania. historia michaliny wisłockiej (2017) 26.10

orphan (2009) 29.10

pearl (2022) 30.10

the exorcist (1973) 31.10

corpse bride (2005) 31.10

the broken hearts gallery (2020) 01.11

adult world (2013) 05.11

marriage story (2019) 09.11

don't worry darling (2022) 11.11

hot tub time machine (2010) 12.11

secret obsession (2019) 16.11

logan lucky (2017) 19.11

the age of adaline (2015) 20.11

the perfect date (2019) 21.11

all together now (2020) 23.11

the guardians of the galaxy holiday special (2022) 25.11

black panther: wakanda forever (2022) 26.11

pokémon detective pikachu (2019) 27.11

hotel for the holidays (2022) 02.12

blue velvet (1986) 11.12

mama (2013) 15.12

glass onion: a knives out mystery (2022) 23.12

holidate (2020) 24.12

insidious: the last key (2018) 31.12

the nun (2018) 31.12

[kolbisneat]

MONTHLY MEDIA: January 2022

First monthly media post of 2022! We’ve had -20 and -30 degree (celsius) days here so loooooots of time spent indoors reading and watching stuff.

……….FILM……….

It’s a Mad, Mad, Mad, Mad World (1963) I didn’t realize this was a 3 and a half hour movie so I’m warning you now. But I’m ALSO here to say I loved every minute of it. ‘Epic comedy’ is the only way to describe it and I really wasn’t expecting it to hold up so well for being a 60 year old movie. So fun, a great ensemble of characters, and an ever-evolving plot. Love it. 

The Mentor (2014) Star Wars from Obi Wan Kenobi’s perspective! It basically takes Episode 4 and intercuts it with scenes from the prequels and the editing (by John Venzon) really sells Kenobi’s tragic relationship to the Skywalkers. Worth checking out and you can watch it here.

Wizardry 1 OVA (1981) I’m not sure how I came across this but it’s been in my YouTube queue for a while (you can watch it all for free here). With a bit of research it looks like it’s based off of a video game and it was a breezy D&D-esque adventure. Some very 80s stuff going on but worth it for some fun battles. Also the main villain is named Werdna and as an Andrew, I immediately knew what was going on (one of the developers is named Andrew so they just reversed his name for the villain). Classic Andrew shenanigans.

Velvet Buzzsaw (2019) There’s some capital “A” Acting going on here and once I understood what the genres were and the general concept, I thought it would be a lot more heightened than it was. Some solid comedy moments but overall, most scenes felt either 1) unnecessary or 2) predictable and that’s no fun to watch. Jake Gyllenhaal, however, is always a delight.  

The Hobbit: The Tolkien Edit (2015) Another fan edit! The Hobbit is dear to my heart and the original trilogy of films never worked for me. This was much better! I still find anything after Smaug to lack the same weight (it is Bilbo’s story, afterall) but this 4.5 hour movie has a lot going for it. I’ve recently discovered there are OTHER edits so I’ll be checking them out next winter. In the meantime you can read more about this edit here.

……….TELEVISION……….

The Bachelor (Episode 26.01 to 26.03) You know I kinda like how dopey Clayton is. Would he have been my number 1 pick for this season? No. Does he have any idea what he’s doing? It doesn’t look like it. Am I enjoying the weird meta game that the main villains are playing? Absolutely.

Dorohedoro (Episode 1.01 to 1.04) It took me a bit to acclimate to the violence (I watch a lot of all-ages cartoons, what can I say) but the world is weird and consistently surprising. And a lot of time is spent on food prep so that’s a win for me. The characters are interesting and that’s enough for me to watch the rest of the season!

Adventure Time: Distant Lands (Episode 1.01 to 1.04) This is exactly what I wanted: self-contained stories that explore individual characters from the main series with a long enough runtime to really explore some fun stuff. I fell off of Adventure Time yeeeeears ago but this was a perfect return and yeah, Together Again got me right in the heart.

The Beatles: Get Back (Episode 1.01 to 1.03) Such a joy to watch. I mean I essentially broke up each ep into 3 or 4 smaller episodes, but that’s just me. The last episode hit particularly hard as not only the series wound down but so too did the Beatles. As a study in seeing how art is made, it felt remarkably honest and for that I appreciate it. Also I never expected to so thoroughly connect with Ringo Starr. Just a low key light that the rest of the band can turn to and rely on.

……….READING……….

Interesting Times by Terry Pratchett (Complete) I love the Discworld series and I love Rincewind as a character so this had a lot going for it. If you get past some of the dated humor around the setting (a mishmash of Asian cultures) then there’s a lot of great commentary about class structure and the power of myth. Perhaps not one of my top Discworld novels but even an okay book by Pratchett is still a joy to read.

Babes in the Wood RPG by Adam Vass and Kim Nguyen (Complete) This should probably go in the gaming section but I have only read through this RPG and not yet played it. Lovely concept and if you like Over the Garden Wall or Adventure Time then I think you’ll dig this. 

Dorothy and the Wizard of Oz by Eric Shanower, Skottie Young, and L. Frank Baum (Complete) Of Baum’s early books I found this was the first dip in enjoyment. Perhaps it’s because it’s a mix of neither being set in Oz nor featuring many of the main characters, but it just feels different. You know? Anyway the adaptation is fantastic and Young’s artwork continues to walk that line between creepy and adorable, as is appropriate for some of the terrors in Oz.

……….AUDIO……….

Bat out of Hell by Meat Loaf (1977) Early Meatloaf will always have a special place in my heart and really I’ve been listening to this and Dead Ringer on repeat since his passing. Such wonderful Drama Student energy.

……….GAMING……….

Spelunky (Mossmouth) I nearly gave up on this but boy howdy am I a fan. I mean I haven’t beaten the final boss and have no plans to try for all of the crazy secrets but right now I’m just happy to explore, set off traps, and see how far I can go. Highly recommend and know that there’s a system in place so you don’t need to start from the first as you get better.

Oz: A Fantasy Role-Playing Setting (Forthcoming, Andrews McMeel Publishing) The Mof1 crew and I play D&D every so often and this month we thought we’d try out Oz! It was intended to be a one-shot but after a second session (and a lot of exposition) I think they’re keen to really dig into the city. Very exciting!

Neverland: A Fantasy Role-Playing Setting (Andrews McMeel Publishing) My weekly group continues to explore Neverland and this month they babysat some seniors and let them wander into another dimension! Whoops. Full campaign diary is over here on reddit.

And that’s it! As always, let me know if you have any recommendations and see you in February!

[llpodcast]

(Literary License Podcast)  Season 1.  Episodes 5 - 8. Samantha offers to help Darren with his soup campaign much to his annoyance.  Samantha helps a neighbourhood boy to gain self-confidence. Witches are being stereotyped by the advertising agency much to the dismay of Aunt Clara, Bertha and Mary.  Darren is putting in overtime leaving a bored Samantha to zip off to Paris with her mother only to meet Mr Tate.  Special Guest Stars include:  Charlie Ruggles, June Lockhart, Jimmy Mathers, Shelly Berman, Reta Shaw, Madge Blake and Marion Lorne. Opening Credits; Introduction (.36.21); Story Geek:  What To Watch During The COVID Crisis (6.55); Bewitching Going On/Which Witch Is Which:  Episode 5 – Help, Help, Don’t Save Me (10.52); Episode 6 – Little Pitchers Have Big Fears (28.20); Episode 7 – The Witches Are Out (44.58); Episode 8 – The Girl Reporter (1:02.28); Witch or Mortal (1:12.43); The Bewitching Hour (1:19.49); The Midnight Hour (1:26.01); End Credits (1:36.21); Closing Credits (1:33.08) Opening Credits– Theme Song from Bewitched Television Show by Jack Keller Closing Credits – Closing Credits from Bewitched Television Show by Jack Keller Copyright owned by Screen Gems. All rights reserved. 

[nuclearblastuk]

NAILED TO OBSCURITY | Band release first tour diary trailer

German melodic death/doom metallers NAILED TO OBSCURITY are  currently on tour with EQUILIBRIUM,  LORD OF THE LOST and OCEANS. Today, the  band releases the first part of their tour diary video series. Watch episode  one to get an insight into the band's life on the road, here: youtu.be/YG6dzzhGLhU    The band comments: "It’s  day 7 on our tour with Equilibrium, Lord Of The Lost and Oceans! We had a  great start and the tour-family is growing more closely together with each  day. The reception by the different audiences has been amazing and it’s cool  to see the different reactions towards all the unique styles within the  tour-package. Today, we’re off to Madrid and we can’t await to see our  Spanish friends and fans again!"    Renegades Tour -  Europe 2020  w/ EQUILIBRIUM, LORD  OF THE LOST, OCEANS (*)  23.01.                 E           Madrid - Sala  Caracol  24.01.                 E           Barcelona -  Sala Bóveda  25.01.                 F           Lyon - Ninkasi  Kao  26.01.                 D          Lindau - Club Vaudeville*  28.01.                 H          Budapest - Dürer Kert  29.01.                 PL         Kraków - Klub Kwadrat  30.01.                 A           Vienna - Szene  31.01.                 D          Munich - Backstage  (Werk)*  01.02.                 CH        Pratteln - Z7*  02.02.                 CZ         Prague - Nová Chmelnice  04.02.                 N          Oslo - John Dee  05.02.                 S           Stockholm -  Fryshuset  06.02.                 DK        Copenhagen - Pumpehuset  07.02.                 D          Cologne -  Essigfabrik*  08.02.                 D          Stuttgart - LKA  Longhorn*  09.02.                 D          Hanover - Capitol*  11.02.                 D          Saarbrücken - Garage*  12.02.                 D          Nuremberg - Hirsch*  13.02.                NL        Eindhoven - Dynamo  14.02.                 UK        London - O2 Academy Islington  15.02.                UK         Birmingham - HRH Metal IV  16.02.                 B           Vosselaar -  Biebob    Black  Frost is available to order on various formats (TS+DIGI BUNDLE, DIGI,  LP), here: nblast.de/NTOBlackFrost    NAILED  TO OBSCURITY is:  Raimund Ennenga  | vocals  Jan-Ole Lamberti |  guitars  Volker Dieken |  guitars  Carsten Schorn  | bass  Jann Hillrichs  | drums  ---  More info:  nailedtoobscurity.com  facebook.com/nailedtoobscurity  nuclearblast.de/nailedtoobscurity

[tosimornottosim]

Scores for Episode 12

Jackie- 36.00 Auburn- 31.54 Mint- 31.44 Prosecco- 30.81 Lichen- 26.01 Felicity- 23.08 Sera- 20.17 Venus- 18.63

[njawaidofficial]

EU Fine Hits Google Second-Quarter Earnings, Sends Stock Down

http://styleveryday.com/2017/07/26/eu-fine-hits-google-second-quarter-earnings-sends-stock-down/

EU Fine Hits Google Second-Quarter Earnings, Sends Stock Down

1:20 PM PDT 7/24/2017 by Natalie Jarvey

The search and advertising giant was hit with a $2.7 billion fine in June for its online shopping business.

Google owner Alphabet saw profit drop during the second quarter due to a $2.7 billion fine levied by European antitrust regulators.

The setback, revealed Monday in the company’s quarterly earnings report, sent the company’s stock down more than 3 percent during afterhours trading on the Nasdaq. 

The search and advertising giant reported earnings of $5.01 per share, down from $7 per share during the same period last year. Adjusted earnings that did not include the fine came in at $8.90 per share.

Revenue was up 21 percent to $26.01 billion. Despite the profit decline, both revenue and earnings were well ahead of Wall Street’s expectations. Analysts had been anticipating earnings of $4.46 per share and revenue of $25.64 billion. 

The European Union issued the fine against Google in June after a seven-year investigation that found the company guilty of favoring its own shopping service’s search results ahead of competitive services. At the time, European Commissioner Margrethe Vestager, head of competition policy for the EU, noted that “Google’s strategy for its comparison shopping service wasn’t just about attracting customers by making its product better than those of its rivals.” At the time, the company said it would consider an appeal. 

Outside of the fine, Google’s strong quarter indicated that troubles with advertisers at YouTube were not material enough to impact its overall business. During the quarter, a Wall Street Journal report said that some YouTube ads were running alongside violent or inappropriate videos, causing some advertisers to pull off of the platform entirely. YouTube made some adjustments to its advertising products to address the concerns and some advertisers have returned, but that didn’t stop investors from questioning how the episode would impact second-quarter earnings. 

“YouTube is one of those products scaling really well globally, just like search did,” said Google CEO Sundar Pichai during Alphabet’s earnings call with investors. “We’re seeing real strong growth on mobile. We’re seeing real strong growth for emerging markets, as well. … I think there’s a lot more growth ahead.” 

Meanwhile, Alphabet’s “other bets” division — which includes acquisitions like Nest and other longer-term projects being developed through its X lab — remains a small revenue driver and unprofitable business. During the second quarter, it brought in revenue of $248 million, up from $185 million during the same quarter last year. Operating loss shrunk to $772 million during the quarter. 

Alphabet stock closed the day up nearly 1 percent to $980.34. 

[saurabhsood-blog1]

Week 3

Not: This is a python program. So it will be longer than a SAS program.

Program:

#!/usr/bin/env python3

# -*- coding: utf-8 -*-

"""

Created on Tue Jun  6 11:10:02 2017

@author: saurabhsood

"""

#!/usr/bin/env python3

# -*- coding: utf-8 -*-

"""

Created on Wed May 31 12:52:57 2017

@author: saurabhsood

"""

import pandas

import numpy

#to avoid runtime error

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

#asking python to read the data

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

#ALCOHOL DEPENDENCE

#using logic statements to restrict my data to people aged under 25, after

#converting it from strings to numeric

data['S2BQ2D']=data['S2BQ2D'].convert_objects(convert_numeric=True)

data.loc[data['S2BQ2D'].isnull(),'S2BQ2D']=99

sub1=data[(data['S2BQ2D']<=30)]

#sub1=data.copy()

sub2=sub1.copy() #create a copy of sub1. This will be the variable that will

#be called in the program, from now on

#asking python to read the values as numeric, and sort them accordingly

sub2['S2BQ2E']=sub2['S2BQ2E'].convert_objects(convert_numeric=True)

sub2['S2DQ1']=sub2['S2DQ1'].convert_objects(convert_numeric=True)

sub2['S2DQ2']=sub2['S2DQ2'].convert_objects(convert_numeric=True)

sub2['S2DQ14A']=sub2['S2DQ14A'].convert_objects(convert_numeric=True)

sub2['S2DQ14B']=sub2['S2DQ14B'].convert_objects(convert_numeric=True)

#printing the frequency tables, not dropping the missing values, not arranging

#in the order of frequency

print('number of episodes of alcohol dependence')

sub2['S2BQ2E']=sub2['S2BQ2E'].replace(numpy.nan,0) #replaced missing value with 0

sub2['S2BQ2E']=sub2['S2BQ2E'].replace(99,numpy.nan) #replaced unknown with nan

c1=sub2['S2BQ2E'].value_counts(sort=False,dropna=False)

print (c1)

print('Blood/natural father ever an alcoholic or problem drinker')

c2=sub2['S2DQ1'].value_counts(sort=False,dropna=False)

print(c2)

print('Blood/natural mother ever an alcoholic or problem drinker')

c3=sub2['S2DQ2'].value_counts(sort=False,dropna=False)

print(c3)

print('Adoptive father ever an alcoholic or problem drinker')

c4=sub2['S2DQ14A'].value_counts(sort=False, dropna=False)

print(c4)

print('Adoptive mother ever an alcoholic or problem drinker')

c5=sub2['S2DQ14B'].value_counts(sort=False,dropna=False)

print(c5)

#defining a function to reduce the number of categories from 4 to 2. Since we 

#are interested in only 1 father (natural or adoptive), and similarly 1 mother,

#so we combine them.

def father(row):

    if row['S2DQ1']==1 or row['S2DQ14A']==1:

        return int(1)

    else: return int(0)

    def mother(row):

    if row['S2DQ2']==1 or row['S2DQ14B']==1:

        return int(1)

    else: return int(0)

    #creating a new data set representing alcoholic father (natural or adoptive) 

print('Natural or Adoptive father ever an alcoholic')  

sub2['ALCOHOLIC_F']=data.apply(lambda row: father(row), axis=1)

c6=sub2['ALCOHOLIC_F'].value_counts(sort=False, dropna=True)

print(c6)

#creating a new data set representing alcoholic mother (natural or adoptive)

print('Natural or Adoptive mother ever an alcoholic')   

sub2['ALCOHOLIC_M']=data.apply(lambda row: mother(row), axis=1)

c7=sub2['ALCOHOLIC_M'].value_counts(sort=False,dropna=True)

print (c7)

#creating a new data set indicating the number of alcoholic parents

print('number of alcoholic parents')

sub2['ALCOHOLIC_P']=sub2['ALCOHOLIC_F']+sub2['ALCOHOLIC_M']

c8=sub2['ALCOHOLIC_P'].value_counts(sort=False)

print(c8)

#printing the cross table with number of alcoholic parents as rows, and number

#of episodes of alcohol dependence as columns

print (pandas.crosstab(sub2['ALCOHOLIC_P'],sub2['S2BQ2E']))

#NO ALCOHOL DEPENDENCE

#This analysis is being done to find out the data on parents whose alcoholism

#didn't affect their children's alcoholism

#using logic statements to restrict my data to people aged over 25

sub1=data[(data['S2BQ2D']>30)]

#sub1=data.copy()

sub2=sub1.copy() #create a copy of sub1. This will be the variable that will

#be called in the program, from now on

#asking python to read the values as numeric, and sort them accordingly

sub2['S2BQ2E']=sub2['S2BQ2E'].convert_objects(convert_numeric=True)

sub2['S2DQ1']=sub2['S2DQ1'].convert_objects(convert_numeric=True)

sub2['S2DQ2']=sub2['S2DQ2'].convert_objects(convert_numeric=True)

sub2['S2DQ14A']=sub2['S2DQ14A'].convert_objects(convert_numeric=True)

sub2['S2DQ14B']=sub2['S2DQ14B'].convert_objects(convert_numeric=True)

print('Blood/natural father ever an alcoholic or problem drinker')

c2=sub2['S2DQ1'].value_counts(sort=False,dropna=False)

print(c2)

print('Blood/natural mother ever an alcoholic or problem drinker')

c3=sub2['S2DQ2'].value_counts(sort=False,dropna=False)

print(c3)

print('Adoptive father ever an alcoholic or problem drinker')

c4=sub2['S2DQ14A'].value_counts(sort=False, dropna=False)

print(c4)

print('Adoptive mother ever an alcoholic or problem drinker')

c5=sub2['S2DQ14B'].value_counts(sort=False,dropna=False)

print(c5)

#defining a function to reduce the number of categories from 4 to 2. Since we 

#are interested in only 1 father (natural or adoptive), and similarly 1 mother,

#so we combine them.

def father(row):

    if row['S2DQ1']==1 or row['S2DQ14A']==1:

        return int(1)

    else: return int(0)

    def mother(row):

    if row['S2DQ2']==1 or row['S2DQ14B']==1:

        return int(1)

    else: return int(0)

    #creating a new data set representing alcoholic father (natural or adoptive) 

print('Natural or Adoptive father ever an alcoholic')  

sub2['ALCOHOLIC_F']=data.apply(lambda row: father(row), axis=1)

c6=sub2['ALCOHOLIC_F'].value_counts(sort=False, dropna=True)

print(c6)

#creating a new data set representing alcoholic mother (natural or adoptive)

print('Natural or Adoptive mother ever an alcoholic')   

sub2['ALCOHOLIC_M']=data.apply(lambda row: mother(row), axis=1)

c7=sub2['ALCOHOLIC_M'].value_counts(sort=False,dropna=True)

print (c7)

#creating a new data set indicating the number of alcoholic parents

print('number of alcoholic parents')

sub2['ALCOHOLIC_P']=sub2['ALCOHOLIC_F']+sub2['ALCOHOLIC_M']

c9=sub2['ALCOHOLIC_P'].value_counts(sort=False)

print(c9)

#total number of alcoholic parents

print('total number of alcoholic parents')

print (c8+c9)

Output:

number of episodes of alcohol dependence nan           192 1.000000     2716 2.000000      524 3.000000      261 4.000000       96 5.000000       76 6.000000       25 7.000000        9 8.000000        5 9.000000        2 10.000000      36 11.000000       1 12.000000      19 14.000000       2 15.000000       9 16.000000       1 17.000000       1 18.000000       2 20.000000      17 21.000000       3 22.000000       4 24.000000       3 25.000000       5 26.000000       2 27.000000       1 29.000000       1 30.000000       3 40.000000       3 50.000000       4 51.000000       1 60.000000       1 62.000000       2 75.000000       1 98.000000      10 Name: S2BQ2E, dtype: int64

number of alcoholic parents with alcoholic children before 30 0    2434 2     333 1    1271 Name: ALCOHOLIC_P, dtype: int64

total number of alcoholic parents 0    33861 1     7954 2     1278 Name: ALCOHOLIC_P, dtype: int64

Summary:

Since I had to study the relationship between family (parents) history of alcoholism, and alcoholism so I restricted the data set to only those people who became an alcoholic before the age of 30. As during that time, they are less likely to get dependent on alcohol due to other factors, which may arise during later stages of life (like problematic marriage, not-so-good career).

Next, I created a new variable which erases the difference between adoptive and natural father and puts them into a common category, ‘father’ which accounts for the fact if any of the fathers was an alcoholic. Similarly ad new category ‘mother’ was also created.

Then I used it to find out the number of alcoholic parents with alcoholic children before 30, the frequency table of which is given above.

Then I created another data set for the remaining people, repeated the entire process, and found out the number of alcoholic parents with non alcoholic children before 30. Then I combined both to get the total number of alcoholic parents, the frequency table of which is given above.

Missing data was for those who never became dependent on alcohol. While setting the restriction on age, I set their age to 99 to avoid them being included in category of alcoholic children before 30.

The results obtained were 7.19% of children with non alcoholic parents became alcoholic before 30, while 15.98% of children with one alcoholic parent became alcoholic before 30, and 26.01% of children with two alcoholic parents became alcoholics before 30.

[arasia2017-blog]

Episode 4: Đà Lạt und Mui Ne (26.01 - 31.01)

Mit dem bislang wackligsten Bus auf der Reise tuckerten wir auf 1500 Meter Höhe nach Đà Lạt. Hier hatten wir zum ersten mal so richtig Sonne und als wir aus dem Bus stiegen dachten wir uns würden jetzt 32 Grad entgegen knallen, allerdings waren es nur milde 22. Da Lat ist eine etwas kleinere Stadt, die selber bis auf einen größeren See, ein paar Museen und nette Restaurant nicht allzu viel zu bieten hat. Etwas außerhalb hiervon kann man aber verschiedene Canyoning- und Trekkingtouren machen. Wir haben also eine solche Tour gebucht und am nächsten Tag ging es los. Früh aufstehen, halbe Stunde fahren, Trekking Ausrüstung angezogen. Als nächstes wurden wir einem wirklich lustigen Tourguide eingewiesen und schon ging es den ersten Wasserfall runter. Das war echt ein unglaubliches Erlebnis. Du steigst mit beiden Händen am Seil, den Beinen in der Hocke, mit ständig Wasser im Gesicht und viel Panik da runter! Am Anfang geht dies noch echt gut, dann erreichte man leider eine Art Schlucht, worin der Schuh bei dem ein oder anderen stecken blieb. Unter anderem ich geriet in Panik, sodass es nicht mehr so sicher nach unten ging und ich mit einem blutigen Bein aus dem ganzen Akt abgeschlossen habe. Darauf folgend ging es mit Canyoning weiter: Also klettern, abseilen und von Klippen ins Wasser springen.

Obwohl die Sonne schien war es irgendwann arschkalt und wir waren froh als wir wieder im warmen waren. Die Tour war dennoch jeden Cent wert und definitiv empfehlenswert.

Irgendwann tuckelten wir früh morgens mit einem sehr schauckligen Bus nach Mui Ne, einem Kite-Surfer Ort. Während dieser Fahrt ereigneten sich allerdings nicht sehr schöne Dinge, denn leider bekamen wir einen schlimmen Unfall mit, bei dem ein Jugendlicher umkam und während wir dran vorbeifuhren auch noch auf der Straße lag, sehr unschön!

Unser Hostel lag direkt am Kite-Strand - der auch wirklich sehr schön ist - bei dem wir uns im Schatten der Palmen bei 32 Grad einen Mittagsschlaf gegönnt haben. Nett. Mui Ne hat einen schönen Strand - zumindest teilweise - Dünen und eine Kilometer lange Straße mit schönen Ecken und nicht so schönen. Die Dünen kann man z.B. für einen Sonnenuntergang bestaunen, was wirklich sehr schön ist. Den Strand kann man einfach genießen und dabei coole Tricks auf den Kites beobachten. Und an der Straße kann man lecker essen. Oder eher gesagt in einem Food-Court kann man sehr lecker essen! Dort gibt es verschiedene Buden, bei denen man sich von Mexikanisch zu Thailändisch zu Indisch verschiedenste Speisen gönnen kann. Sehr lecker!

[nuclearblastuk]

BEHEMOTH | 'Ecclesia Diabolica Catholica' music video, European tour kick off

After recently completing a North American headlining tour with AT THE GATES and WOLVES IN THE THRONE ROOM, BEHEMOTH will be bringing this must-see show to Europe, starting tomorrow! In anticipation of the trek, the band has also launched a new video for 'Ecclesia Diabolica Catholica' (directed by Grupa 13 / www.grupa13.com), taken from their latest album, 'I Loved You At Your Darkest'. To watch the clip, please visit:https://youtu.be/HKWqzjQAv14 

Orion (bass & vocals) comments: "BEHEMOTH Legions! As this 'ILYAYD' adventure continues onwards, we want to share a new video with you! Since we began the writing process, 'Ecclesia Diabolica Catholica' was a stand-out contender to be featured as a single and music video. As the song evolved during rehearsal and recording, it gained this lively, furious vibe...which you hear now - thus, it includes live performance elements which we've not done in quite some time. We are happy to work with Grupa13 once again - and once again, they showed their super-professional approach at every step of the shooting and video production. Two separate locations, hours of preparation, but it was all worth it. In absentia dei, we evangelize! Enjoy!"

See below for all dates! Tickets can be purchased at: http://www.behemoth.pl 

"Ecclesia Diabolica Evropa 2019 e.v." BEHEMOTH AT THE GATES WOLVES IN THE THRONE ROOM

10.01. D Frankfurt - Batschkapp 11.01. D Munich -TonHalle 12.01. CZ Prague - Forum Karlín 13.01. A Vienna - Arena *SOLD OUT* 15.01. CH Zurich - Komplex 457 16.01. I Milan - Alcatraz 17.01. F Lyon - Le Transbordeur 18.01. E Barcelona - Razzmatazz 19.01. E Madrid - Sala Riviera 21.01. F Toulouse - Le Bikini 22.01. F Paris - Bataclan 23.01. D Oberhausen - Turbinenhalle 24.01. D Berlin - Huxleys Neue Welt 25.01. DK Copenhagen - Vega 26.01. S Stockholm - Annexet 27.01. N Oslo - Rockefeller Music Hall 29.01. FIN Helsinki - The Circus 30.01. FIN Tampere - Pakkahuone 01.02. D Hamburg - Große Freiheit 36 02.02. NL Utrecht - TivoliVredenburg (Ronda) 03.02. B Brussels - Ancienne Belgique 04.02. LUX Esch-sur-Alzette - Rockhal 06.02. UK Bristol - Motion 07.02. UK Birmingham - O2 Institute 08.02. UK London - O2 Forum Kentish Town 09.02. UK Manchester - O2 Ritz *SOLD OUT* 10.02. IRL Dublin - Vicar Street 11.02. UK Glasgow - Queen Margaret Union

'I Loved You At Your Darkest'  is a crushing salvo of black metal majesty replete with hellish riffs, thundering drum cannonades and soaring liturgical choirs reminiscent of classic horror cinema. BEHEMOTH's most dynamic record yet, the album is extreme and radical on one hand, but also more rock-oriented than any other release. Produced by the band themselves, with drum co-production by Daniel Bergstrand (MESHUGGAH, IN FLAMES), mixing by Matt Hyde (SLAYER, CHILDREN OF BODOM) mastering by Tom Baker (NINE INCH NAILS, MARILYN MANSON), and a 17-piece Polish orchestra arranged by Jan Stoklosa, 'I Loved You At Your Darkest' can be previewed and purchased now at: http://behemoth.lnk.to/ILYAYD

BEHEMOTH line-up: Nergal - vocals & guitars Orion - bass & vocals Inferno - drums & percussion http://www.behemoth.pl http://www.facebook.com/behemoth http://instagram.com/behemothofficial http://www.nuclearblast.de/behemoth http://www.metalblade.com/behemoth

ICYMI: Episode 1 ('God=Dog'): https://youtu.be/pxmijeqkFiU Episode 2 (Cover/Artwork): https://youtu.be/x9SrlcbJ3II Episode 3 ('Wolves Ov Siberia'): https://youtu.be/UNObEyGOsXE Episode 4 (Provocation): https://youtu.be/joPot91iGm4 Episode 5 (Darkness): https://youtu.be/YxyakPvsPMM Episode 6 (100% Danzig): https://youtu.be/rWjXrUmsJ94 'God=Dog' music video: https://youtu.be/Sf5GmhffA48 'Wolves Ov Siberia' music video: https://youtu.be/g7yxjTcM7Bs 'Bartzabel' music video: https://youtu.be/ZjYIRui5gtY