enumerate

languages = ['Python', 'C', 'C++', 'C#', 'Java']

#Bad way
i = 0 #counter variable
for language in languages:
    print(i, language)
    i+=1

#Good Way
for i, language in enumerate(languages):
    print(i, language)

for index,subj in enumerate(subjects):
    print(index,subj) ## enumerate will fetch the index
    
0 Statistics
1 Artificial intelligence
2 Biology
3 Commerce
4 Science
5 Maths

presidents = ["Washington", "Adams", "Jefferson", "Madison", "Monroe", "Adams", "Jackson"]
for num, name in enumerate(presidents, start=1):
    print("President {}: {}".format(num, name))

for index,char in enumerate("abcdef"):
  print("{}-->{}".format(index,char))
  
0-->a
1-->b
2-->c
3-->d
4-->e
5-->f

for key, value in enumerate(["p", "y", "t", "h", "o", "n"]):
    print key, value

"""
0 p
1 y
2 t
3 h
4 o
5 n
"""

# Python program to illustrate 
# enumerate function 
l1 = ["eat","sleep","repeat"] 
s1 = "geek"
  
# creating enumerate objects 
obj1 = enumerate(l1) 
obj2 = enumerate(s1) 
  
print "Return type:",type(obj1) 
print list(enumerate(l1)) 
  
# changing start index to 2 from 0 
print list(enumerate(s1,2)) 

# Python program to illustrate 
# enumerate function in loops 
l1 = ["eat","sleep","repeat"] 
  
# printing the tuples in object directly 
for ele in enumerate(l1): 
    print ele 
print 
# changing index and printing separately 
for count,ele in enumerate(l1,100): 
    print count,ele 
Output:

(0, 'eat')
(1, 'sleep')
(2, 'repeat')

100 eat
101 sleep
102 repe

# Python program to illustrate 
# enumerate function 
l1 = ["eat","sleep","repeat"] 
s1 = "geek"
  
# creating enumerate objects 
obj1 = enumerate(l1) 
obj2 = enumerate(s1) 
  
print "Return type:",type(obj1) 
print list(enumerate(l1)) 
# Changing start index to 2 from 0 
print list(enumerate(s1,2)) 

#These are the outputs
Return type: < type 'enumerate' >
[(0, 'eat'), (1, 'sleep'), (2, 'repeat')]
[(2, 'g'), (3, 'e'), (4, 'e'), (5, 'k')]

words=['zero','one','two']
for operator, word in enumerate(words):
	print('%s %s' %(word, operator))

categorical_features_new=[features for features in df.columns if df[features].dtypes=='object']
for feature in categorical_features_new:
    labels_sorted=df[feature].value_counts().sort_values().index
   
    labels_ordered={k:i for i,k in enumerate(labels_sorted,0)}
    
    df[feature]=df[feature].map(labels_ordered)