There are many inbuilt functions and methods in python. Here are a few of the crucial functions:

**1. Replace( ): **The replace( ) method creates a replica of the string by replacing every instance of one substring with a different substring**. **It returns a new string where all the old substrings are replaced with a new substring.

**Syntax: **string.replace(old, new, count)

Old: old substring that we want to replace

New: old substring will be replaced with this new substring

Count: The number of times we want to replace the old with a new substring

**Examples and uses: **

*## Replace all ‘two’ with ‘four’*

Sample=”one, two, three, one, two, three, one, two, three”

Sample.replace(‘two’, ‘four’)

*## Replace only first ‘two’ with ‘four’*

Sample=”one, two, three, one, two, three, one, two, three”

Sample.replace(‘two’, ‘four’, 1)

- Replace function is very helpful in handling missing values in a data frame.

import numpy as np

import pandas as pd

*# will replace Nan value in dataframe with value 99 *

data.replace(to_replace = np.nan, value = 99)

*#Replace the null values with the mean:*

df[‘A’].replace([numpy.nan], df[A].mean(), inplace=True)

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**2.** **Map: **The map function** **applies the given function to each item of a given iterable (list, tuple, etc.)

**Syntax**: map(function, iterables)

Function: a function that performs some action on each element of an iterable

Iterables: an iterable like sets, lists, tuples, etc

**Examples and uses: **

- ##
*Program to add number with itself*

def addition(n):

return n + n

numbers = (1, 2, 3, 4)

result = map(addition, numbers)

list(result)

- ##
*To add two different numbers (we can pass multiple iterables also)*

def addition(n1,n2):

return n1 + n2

n1 = (1, 2, 3, 4)

n2=(3,4,6,8)

result = map(addition, n1,n2)

list(result)

- ##
*Map with lambda function*

num = (1, 2, 3, 4)

result = map(lambda x: x + x, num)

list(result)

- The map function can be used to change categorical values to numerical values in the data frame.

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**3.** **Format( ): **The format function is used to format any string.

**Syntax: ***string*.format(*value1, value2…*)

The format() method formats the specified value(s) and insert them inside the string’s placeholder. The placeholders can be identified using named indexes {name}, numbered indexes {1}, or even empty placeholders {}.

**Examples and uses: **

str1 = “My name is {fname}, I’m {age}”.format(fname = “Jack”, age = 20)

str2 = “My name is {0}, I’m {1}”.format(“Jack”,20)

str3 = “My name is {}, I’m {}”.format(“Jack”,20)

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**4.** **Apply ( ): **Apply function can be treated as an alternative to loops in data frames and series. It applies a function on each element in a pandas Series and each row or column in a pandas DataFrame.

** Syntax: **s.apply(function, convert_dtype=True, args=())

Function: Function to apply to each column or row.

s: series/Dataframe

**Examples and uses: **

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**5.** **Filter**: This function verifies whether each element in the series is true or false,

**Syntax**: filter(function, sequence)

function: function that tests if each element of a sequence is true or not.

sequence: sequence like sets, lists, tuples, or containers of any iterators.

**Examples and uses: **

- ## Program to return the ages that are greater than 18

ages = [6, 13, 16, 19, 25, 33]

def age(x):

if x < 18:

return False

else:

return True

adults = filter(age, ages)

for x in adults:

print(x)

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**6.** **Range**: It is used to return a sequence of numbers.

**Syntax: **range*(start, stop, step*)

Start: The integer number specifying with which number to start. By default, it is 0.

Stop: The integer number specifying the last number.

Step: An integer number specifying the incrementation. By default, it is 1.

**Examples and uses: **

- ##
*printing numbers from 3 to 20 with increments of 2*

for i in range(3,20,2):

print(i, end=” “)

output: 3 5 7 9 11 13 15 17 19

*## performing sum of natural number*

sum = 0

for i in range(1, 11):

sum = sum + i

print(“Sum of first 10 natural number :”, sum)

Output: Sum of first 10 natural numbers: 55

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**7.** **Isinstance( ): **This function** **returns True if the object is specified types, and it will not match then return False.

**Syntax**: isinstance(obj, class)

**Examples and uses: **

numbers = [1, 2, 3]

result = isinstance(numbers, list)

print(numbers,’instance of list?’, result)

Output: [1, 2, 3] instance of list? True

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**8.** **Any and All**

**Any** Returns True if any of the items is True and returns False if empty or all are false. It can be thought of as – a sequence of OR operations.

**Syntax**: any(iterable)

**Examples and uses: **

- print (all([True, True, True, True]))

print (all([False, True, True, False]))

output: True

False

- ##
*It can be used to replace loops*

for element in some_iterable:

if element:

return True

return False

The above code can be written as:

print(any([2 == 2, 3 == 2]))

print(any([True, False, False]))

print(any([False, False]))

output: True

True

False

**All:** It can be thought of as – a sequence of And operations. It returns True if all of the items are True.

**Syntax**: all(iterable)

**Examples and uses: **

- print (all([True, True, True, True]))

print (all([False, True, True, False]))

Output: True

False

*## Can be used in place of loops*

for element in iterable:

if not element:

return False

return True

The above code can be written as:

print(all([2 == 2, 3 == 2]))

print(all([2 > 1, 3 != 4]))

print(all([True, False, False]))

print(all([False, False]))

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**9.** **Zip ( ): **The zip() function in Python creates a single iterator object that contains the mapped values from different containers. It is used to map the index of several containers so that a single entity can access all of them.

**Syntax: **zip(*iterator1, iterator2, iterator3 …*)

**Examples and uses: **

- a = (“John”, “Charles”, “Mike”)

b = (“Jenny”, “Christy”, “Monica”, “Vicky”)

x = zip(a, b)

print(tuple(x))

output: ((‘John’, ‘Jenny’), (‘Charles’, ‘Christy’), (‘Mike’, ‘Monica’))

**10.** **Append**: The Python List append() method is used for adding elements to the end of the List.

**Syntax: **list.append(item)

**Examples and uses: **

a = [“apple”, “banana”, “cherry”]

b = [“Ford”, “BMW”, “Volvo”]

a.append(b)

output: [‘apple’, ‘banana’, ‘cherry’, [‘Ford’, ‘BMW’, ‘Volvo’]]

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