10 Python Built-in Functions Which You Should Know While Learning Data Science

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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