[what] More Program Control Structures In Python







  • IF
    • IF ELIF
    • IF ELIF ELSE
  • WHILE
    • BREAK
    • CONTINUE
    • ELSE
  • FOR
    • FOR ... IN
    • FOR ... IN RANGE
    • ELSE

Most of the examples below used Lambda to iterate through Iterable Object values and process them. Some results are then passed into Map, Filter, and Reduce functions. Further reading: (1) Lambda, (2) Iterable Objects, (3) Map, Filter, and Reduce functions.

...
print ("\n====================\n")
print ("This program displays list in vertical order.")
def printListVertically(list):
  for item in list:
    print (item)

print ("\n====================\n")

text='''called cust care but no response
so far so good :-)
very low power processor
there is no option to activate in the website
no problem at all
i don't know why it is so complicated :(
don't know how to contact them now  :(
customer service is also good
i don't think they allow it these days :-(
didn't know that you can do it
that's really good to know
very happy now :)
so happy with the services
but I found that the rates were very low'''

listSentence=text.split("\n")
print ("Sample sentences:")
printListVertically(listSentence)

print ("\n====================\n")
dictEmoticon={":-)":"pos",":)":"pos",":-(":"neg",":(":"neg"}
print ("Emoticons and their polarities:")
# use zip function to convert dictionary to list object
listEmoticon=list(zip(dictEmoticon.keys(), dictEmoticon.values()))
printListVertically(listEmoticon)

print ("\n====================\n")
# use lambda to iterate through object item, filter their values and convert to dict
dictPositiveEmoticon  = dict(filter(lambda x:x[1] in ['pos'],listEmoticon))
print ("Positive Emoticons:")
printListVertically(dictPositiveEmoticon)
# alternative:
# dictfilt =lambda x,y: dict([ (i,x[i]) for i in x if x[i]=='pos' ])
# dictPositiveEmoticon= dictfilt(dictEmoticon,"pos")
# print(dictPositiveEmoticon)


print ("\n====================\n")
# (1) IF
def findEmoticon(sentence):
  found=False
  # for each emoticon in dictionary, find them in sentence
  for emoticon in set(dictEmoticon.keys()):
    if (emoticon in sentence):
      found=True
  return found  
# use lambda to iterate through object item and then filter their values  
listEmoticonFound= filter(lambda element:findEmoticon(element)==True,listSentence)
print ("Sentences containing emoticons:")
printListVertically(listEmoticonFound)

print ("\n====================\n")
# (2) IF ELIF
def findHappyToken(sentence):
  found=False
  # tokenize sentence
  listWord=sentence.split()
  #print(listWord)
  # if there is any token in listWord matches with token in positive emoticon dictionary
  if (any(substring in listWord for substring in dictPositiveEmoticon)):
    found=True
  #if there is any token in listWord matches with token in happy list
  elif (any(substring in listWord for substring in ['happy'])):
    found=True
  return found  

# use lambda to iterate object item and then filter their values  
listHappyTokenFound= filter(lambda element:findHappyToken(element)==True,listSentence)
print ("Sentences containing happy tokens:")
printListVertically(listHappyTokenFound)

print ("\n====================\n")
# (3) IF ELIF ELSE
def findHappySentence(sentence):
  emotion=''
  # tokenize sentence
  listWord=sentence.split()
  # if there is any token in listWord matches with token in positive emoticon dictionary
  if (any(substring in listWord for substring in dictPositiveEmoticon)):
    emotion='happy'
  #if there is any token in listWord matches with token in happy list
  elif (any(substring in listWord for substring in ['happy'])):
    emotion='happy'
  else:
    emotion='unknown'
  return "["+emotion+"]"+sentence 
# use lambda to iterate through object item and then map their values  
listHappySentence=map( lambda element:findHappySentence(element),listSentence)
print ("Sentences and their happy emotions:")
printListVertically(sorted(listHappySentence))

print ("\n====================\n")


~


python, colab, trinket, jupyter, control structures, lambda, text analysis python, colab, trinket, jupyter, control structures, lambda, text analysis python, colab, trinket, jupyter, control structures, lambda, text analysis python, colab, trinket, jupyter, control structures, lambda, text analysis python, colab, trinket, jupyter, control structures, lambda, text analysis python, colab, trinket, jupyter, control structures, lambda, text analysis python, colab, trinket, jupyter, control structures, lambda, text analysis python, colab, trinket, jupyter, control structures, lambda, text analysis python, colab, trinket, jupyter, control structures, lambda, text analysis

Post a Comment

0 Comments