Commonly used List methods in Python

Below are the basic frequently used methods of List

list1 = [1,2,3]
list1.append(3)
print('1.Append: After appending value 3 at the end of list1 : ',list1)
Output:

1.Append: After appending value 3 at the end of list1 :  [1, 2, 3, 3]

list2 = [10,11]
list1.append(list2)
print('\n2.Append: After appending list2 with list1 : ',list1)
Output

2.Append: After appending list2 with list1 :  [1, 2, 3, 3, [10, 11]]

list1.insert(5,4)
print('\n3.Insert: After inserting value 4 at postion 5 : ',list1)
Output

3.Insert: After inserting value 4 at postion 5 :  [1, 2, 3, 3, [10, 11], 4]

list1.insert(6,list2)
print('\n4.Insert: After inserting value list2 [10,11] at postion 6 : ',list1)
Output

4.Insert: After inserting value list2 [10,11] at postion 6 :  [1, 2, 3, 3, [10, 11], 4, [10, 11]]

a= list1.count([10,11])
print('\n5.Count: Count the occurance of sublist [10,11] in list1: ',a)
Output:

5.Count: Count the occurance of sublist [10,11] in list1:  2

list1.pop()
print('\n6.Pop: Poping up of last item of the list:',list1)
Output:

6.Pop: Poping up of last item of the list: [1, 2, 3, 3, [10, 11], 4]

list1.extend(list2)
print('\n7.Extend: Append will add as element whereas Extend will add as value:',list1)
Output:

7.Extend: Append will add as element whereas Extend will add as value: [1, 2, 3, 3, [10, 11], 4, 10, 11]

print('\n8.Reverse: List before sorting :',list2)
list2.sort(reverse=True)
print('\n8.ReverseList after sorting :',list2)
Output:

8.Reverse: List before sorting : [10, 11]

8.ReverseList after sorting : [11, 10]

i=list1.index(3)
print('First occurance of 3 in the list', i)

Output:

First occurance of 3 in the list 2

print('To use Min or Max from list, list should not be nested list')
print('Minimum from the list2 :', min(list2), '\nMaximum from the list2  :', max(list2))
Output:

To use Min or Max from list, list should not be nested list

Minimum from the list2 : 10

Maximum from the list2  : 11

print('del and Remove, del take index, remove take value to be deleted from list')
print('Before Del, list1 is :', list1)
del list1[0]
print('Del 0 index element from the list, new list :', list1)
list1.remove([11,10])
print('After removing [10,11] from the list1 :', list1)

Output:

del and Remove, del take index, remove take value to be deleted from list

Before Del, list1 is : [1, 2, 3, 3, [11, 10], 4, 10, 11]

Del 0 index element from the list, new list : [2, 3, 3, [11, 10], 4, 10, 11]

After removing [10,11] from the list1 : [2, 3, 3, 4, 10, 11]

Data Science with…Python J

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Deepcopy in Python

If any list is made from existing list then changing the existing list also changes the list which is formed using reference list, to avoid this situation deepcopy function is used to form the resultant list

Problem with below code, here the list c is made from

C = [a,b], which refer to the memory of a and b to get its value and that is the reason when a or b value changes the c list value also gets change.

a = ['neha','sharma']
b=[10,12]
print('a location:', id(a), ' b location:', id(b))
c=[a,b]
print('c list [a,b]:', c, ' c location :', id(c))
b.insert(2,13)
print('b after inserting 13', b)
print('b locatiton after inserting new value :', id(b))
print('c after changing b :  ',c, ' c location after change :', id(c))

Output

a location: 2639312  b location: 2640472

c list [a,b]: [['neha', 'sharma'], [10, 12]]  c location : 2996424

b after inserting 13 [10, 12, 13]

b locatiton after inserting new value : 2640472

c after changing b :   [['neha', 'sharma'], [10, 12, 13]]  c location after change : 2996424

Now, instead of creating new list with z= [x,y] , lets apply copy.deepcopy function, it will copy the content of list instead of referring to the list location , see below in the example

import copy
x=[1,2]
y=[4,5]
z=[copy.deepcopy(x),y]
print('Element of Z :', z)
print('\nLets change the value of X list, by appending')
x.append([3,6])
print('Value of X after appending another list:', x)
print('Now lets check the value of Z :',z)

Output:

Element of Z : [[1, 2], [4, 5]]

Lets change the value of X list, by appending

Value of X after appending another list: [1, 2, [3, 6]]

Now lets check the value of Z : [[1, 2], [4, 5]]

Here if you see, the value of c list didn’t change even though we changed the value of x that is because we took deepcopy of x list while creating the z list.

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List is mutable in Python

Lets check this out by writing a small script, which will create two list and copy both the list to form another list.

a = ['neha','sharma']
b=[10,12]
print('a location:', id(a), ' b location:', id(b))
c=[a,b]
print('c list [a,b]:', c, ' c location :', id(c))

Output:

a location: 14501328  b location: 14502488

c list [a,b]: [['neha', 'sharma'], [10, 12]]  c location : 51493064

Now lets insert a value at the end of second list that is b and check if it is affecting list c

b.insert(2,13)
print('b after inserting 13', b)
print('b locatiton after inserting new value :', id(b))
print(id(c))

Output

b after inserting 13 [10, 12, 13]

b locatiton after inserting new value : 14502488

c after changing b :   [['neha', 'sharma'], [10, 12, 13]]  c location after change : 51493064

Here we can see, changing the list of b, changed the list of c, without changing the memory location. So here we can see list is mutable.

Complete Code:

a = ['neha','sharma']
b=[10,12]
print('a location:', id(a), ' b location:', id(b))
c=[a,b]
print('c list [a,b]:', c, ' c location :', id(c))
b.insert(2,13)
print('b after inserting 13', b)
print('b locatiton after inserting new value :', id(b))
print('c after changing b :  ',c, ' c location after change :', id(c))

But what if we don’t want c to get changed with the change in b…. let’s check this in next post..

Data Science with…Python J

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Reversing a string in Python

It is quite simple in Python, it can be done easily using step parameter of string extract

>>> str = 'reverse'

>>> str[::-1]

'esrever'

With the help of step = -1, we can easily reverse any string in python.

Lets create a function, which will reverse the given string and then check if reverse = actual then return true else false.

def reverseStr(str):
    if str[::-1] == str:
        print('The result is True')
    else:
        print('The result is False')

str = 'liril'
reverseStr(str)

Output:

True

So here you can assign str with value ‘liril’ which in turn is passed to the function and the result was equal to the reverse of the string passed that’s why the result was true.

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How immutable objects are treated in python function

ImMutable: An immutable object can’t not be changed after it is created, example are: any build-in datatype-int, float, str, bool, tuple)

What exactly it means that, when you declare and initialize any immutable variable, it preserve a space in the memory, and the moment you change the value of the variable, modified value get a new  space in memory.

>>> a=3

>>> a

3

>>> id(a)

1812388048

>>> a=a+2

>>> a

5

>>> id(a)

1812388080

>>> type(a)

<class 'int'>

Here in above example if you see, Variable “a” is initialized with value 3 and it occupies memory address of 1811288048, and the moment we tried to update the value of Variable ‘a’ to 5, the modified value i.e. 5 gets a  new memory space which is 1812388080, that is because of immutable characteristics of int datatype.

Now lets create a function, here the function takes a parameter of int type

def updateNumber(n):
    print(id(n))
    n+=10
    print(n)

lets try to call the function with a int variable

def updateNumber(n):
    print('Inside function, before modifying value of a, Mem address of n = ',id(n))
    n+=10
    print('Value of a inside function after modification =', n)

a=5
print('Before calling function Mem address of a = ', id(a))
updateNumber(a)
print('Value of a after calling function = ', a)

Output:

Before calling function Mem address of a =  1812388080

Inside function, before modifying value of a, Mem address of n =  1812388080

Value of a inside function after modification = 15

Value of a after calling function =  5

Here if you see, the location of n inside the function is same as location of a, before calling function i.e. 1812388080, then function modify the value of n from 5 to 15 so inside function when we tried to print the value of n, it gave 15. But once we came out of function and tried to print the value of a, it still gave 5 unchanged.

That means modification of value inside function was not retained outside function. Lets find out why .. by printing a location of n after modifying the value of n in function.

def updateNumber(n):
    print('Inside function, before modifying value of a, Mem address of a = ',id(n))
    n+=10
    print('Inside function after modification of value of n, location of n is = ', id(n))
    print('Value of a inside function after modification =', n)

a=5
print('Before calling function Mem address of a = ', id(a))
updateNumber(a)
print('Value of a after calling function = ', a)
print('After calling function Mem address of a = ', id(a))

Output:

Before calling function Mem address of a =  1812388080

Inside function, before modifying value of a, Mem address of a =  1812388080

Inside function after modification of value of n, location of n is =  1812388240

Value of a inside function after modification = 15

Value of a after calling function =  5

After calling function Mem address of a =  1812388080

Here we can see, the location of n inside function was same as a outside function but the moment function modifies the value of n, it took a separate location and that is the reason why a value even after modifying it inside function didn’t change.

The reason behind this kind of behavior is datatype int is immutable.

Data Science with…Python J

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