Manan

Yesterday, I saw a long dream. I don't know what my biggest fear is but, that was one of the scariest dream I have seen in long time. I don't usually dream and I have stopped dreaming even in the day(I am not a day dreamer anymore). Anyway, I realized that I don't fear death. I may feel pain and I may cry, I may worry about nearones, I may fear uncertainty but there is a good chance that I am not that much afraid of death. But, I was always fond of respect or image. In my dream, I had lost respect and image, love from nearones but I realized that you don't die from such losses. The dream supported nihilistic philosophy. It does not matter much, no matter what you do. That's why there are so many kinds of people and they still manage to not matter much. "There are so many types of people in the world and yet, they manage to not matter much." Therefore, never ever think that you can't live without something or someone. Because, You can and you wi...

Magandang gabi - Good Evening kabayam, ka - friend mahal - love mahal kita - I love you matalina - smart maganda - beautiful tulog - sleep putik - mud bakit - why?

Beautifulsoup findAll(tag, attributes, recursive, text, limit, keywords) find(tag, attributes, recursive, text, keywords) .findAll({"h1","h2","h3","h4","h5","h6"}) .findAll("span", {"class":"green", "class":"red"}) .findAll(text="the prince") .findAll(id="text") Both are same bsObj.findAll(id="text") bsObj.findAll("", {"id":"text"}) Both are same bsObj.findAll(class_="green") bsObj.findAll("", {"class":"green"}) from urllib.request import urlopen from bs4 import BeautifulSoup html = urlopen("http://www.pythonscraping.com/pages/page3.html") bsObj = BeautifulSoup(html) for child in bsObj.find("table",{"id":"giftList"}).children:     print(child) from urllib.request import urlopen from bs4 import BeautifulSoup html...

Konnichiwa - Hello sayonara - bye arigato - thank you baka - idiot hai - yes iie - no gommenasai - sorry matane - see you later oyasumi - good night ikou - let's go chaousi wadou - what's up? kudasai - please kampai - bottom's up watashi - I anata - you da me - oh no

Shiro - Don't (do that) Kaamchakiya - That surprised me Anyong - Hello ye - yes aanio - no na - I ne - my dangsin - you dangsine - your hwanyong haeyo - welcome butak habnida - Please mian haeyo - sorry goma woyo - thanks gapsida - let's go hapsida - let's do it khambe - bottom's up fighting - for cheering urpose ottoke - how? yojim ottoke jineyo? - How are you? nappun - bad najunge - later najungewoyo - see you later irumin boya? - what's your name? busshun ireyo?  - what happened? yerobun - everyone

import numpy as np import pandas as pd df = pd.DataFrame({'List1':[1,2,3, 4,5,5,11,4],'List 2':[3,5,6,8,9,3,4,9]}, columns=['List1', 'List 2']) #df.to_excel("list1.xlsx", header=True, index=False) df['Intersect']=pd.DataFrame( np.intersect1d(df['List1'], df['List 2'])) #unique common in both df['commonin1']=df['List1'][ np.in1d(df['List1'], df['List 2'])] #non unique common items of list 1 df['commonin2']=df['List 2'][np.in1d(df['List 2'], df['List1'])] #non unique common items of list 2 df['1not2']=pd.DataFrame(np. setdiff1d(df['List1'], df['List 2'])) #in list1 but not in list 2 df['2not1']=pd.DataFrame(np. setdiff1d(df['List 2'], df['List1'])) #in list 2 but not in list1 df['1not2NU']=df['List1'][~np. in1d(df['List1'], df['List 2'])] #in list1 but not in list 2 non unique d...

https://gist.github.com/gauravmeena0708/78770ccffb0e008cf25b0261e47fb7d8   https://gist.github.com/gauravmeena0708/71a64e34a8e1a0e49927a288cfb3d7a8   https://gist.github.com/gauravmeena0708/4f3e6c1009dec4446ff93ac011be26cf   data = 'a,b,c \n 1,2,3 \n 4,5,6 \n 7,8,9' pd . read_csv ( StringIO ( data ), names = [ 'foo' , 'bar' , 'baz' ], header = 0 )   data = 'skip this skip it \n a,b,c \n 1,2,3 \n 4,5,6 \n 7,8,9' pd . read_csv ( StringIO ( data ), header = 1 )   pd . read_csv ( StringIO ( data ), usecols = [ 'b' , 'c' ]) pd . read_csv ( StringIO ( data ), usecols = [ 0 , 2 , 3 ]) pd . read_csv ( StringIO ( data ), usecols = lambda x : x not in [ 'a' , 'c' ])     data = ' \n a,b,c \n \n # commented line \n 1,2,3 \n\n 4,5,6' pd . read_csv ( StringIO ( data ), comment = '#' )       data = 'a,b,c \n\n 1,2,3 \n\n\n 4,5,6' pd . read_csv ( StringIO ...