Python high-order function usage summary!

**Author: Super Paper money, Xiamen University, Datawhale original author **

This article is about 2000 words, it is recommended to read it for 6 minutes**

Reviewer: Yuanhao Geng, member of Datawhale, East China Normal University, core contributor to the open source tutorial "Joyful-Pandas".

This article explains in detail the use of the 5 built-in higher-order functions of Python combined with various practical examples, which can help understand the data structure of Python and improve the efficiency of data processing. The 5 functions are:

• map
• reduce
• filter
• sorted/sort
• zip

One, map

1.1 Syntax

The basic syntax of map function is map(func, seq), and its meaning means: execute the function of the previous function func for each element in the iterable sequence, and finally obtain a new sequence. note:

• Python2 directly returns a list
• What is returned in Python3 is an iterator, If you want to return a list, you can use list() to process

help(map)  #View help information

1.2 demo

Illustrate how to use the map function with examples

1. Use Python built-in functions

1. Use custom functions

1. Use anonymous function lambda

There can be multiple parameters when using anonymous functions

Two, reduce

2.1 Syntax

Definition of reduce function:

reduce(function, sequence [, initial])-> value

reduce takes an element from sequence in turn, and uses the result of the last call to function as a parameter, and calls function again.

"When calling a function for the first time, if the initial parameter is provided, the function will be called with the first element in the sequence and initial as the parameters, otherwise it will be called with the first number of the sequence
”

**2.2 Use **

In Python3, the reduce function has been moved to the functools module, and it needs to be imported first:

from functools import reduce   #Import

help(reduce)  #View help documentation

In the above example, we use a graphic to explain:

2.3 demo

1. Use custom functions

1. Use anonymous function lambda

image-20201024185550970

1. A complex example

The specific process is:

1.1*2+1=32.3*3+1=10 # The first 3 is the result 3 above, and the second is 33 in the original data.10*4+1=41

1. Example with initial value

The initial value and the first value in the sequence execute the func function, and the result will be the next starting value

# The specific process is explained as

1.6+1=72.7+2=93.9+3=124.12+4=165.16+5=21

Three, filter

3.1 Syntax

The filter() function is used to filter the sequence, filter out those elements that do not meet the conditions, and return the elements that meet the conditions to form a new list.

Each element in the sequence is passed as a parameter to the function for judgment, returns True or False, and finally the element that returns True is placed in the new list.

filter() syntax is as follows:

filter(function, iterable)  #The former is a function, the latter is a sequence to be executed

3.2 demo

help(filter)  #Help document

1. Use custom functions

Return even numbers within 10

1. Use anonymous function lambda

1. Filtering of strings

Select a string that meets the specified requirements

Four, sorted

4.1 Syntax

sorted(iterable, key=None, reverse=False)

4.2 3 Parameters

sorted() accepts 3 parameters, returns a sorted list

• Iterable object iterable
• reverse=False, accept a Boolean value, choose whether to reverse the sorting result, the default is False
• Accept a callback function key=None, the callback function can only have one parameter, sorted according to the return value of the function

4.3 demo

help(sorted)  #Help document

1. Not inverted by default

1. Sorting tuples, range objects, dictionaries

4.4 Result reversed

The meaning of result reversal is sort the results in descending order, because the original default is ascending order, and reverse=True is used.

4.5 Understanding key

The function of the key parameter is that we customize a function, and then sort by applying the elements in the sequence to the function

Here we use absolute value function

4.6 Contrast sort()

The sort() method can only sort the original list, and the parameters are the same as sorted

The result is that the original list is directly modified in place, while sorted is to generate a new list, the two are different

Five, zip

zip() is a very important method in Python, which can quickly implement many functions.

5.1 Syntax

zip([iterable,...])  #iterable is one or more iterators

• The result of function execution is a zip object returned in Python3. If you need to display it in the form of a list, use the list method to expand directly; The expanded result is in the form of nested tuples in the list
• What is returned directly in Python2 is in the form of tuple list

help(zip)  #View document

5.2 zip accepts a sequence

zip can accept lists, tuples, strings and other forms

zip accepts the form of an empty list, and the returned list is still empty

5.3 zip accepts multiple sequences

Simultaneously merge different types of sequences

5.4 Different processing length

When multiple sequences exist at the same time, take the length of the smallest sequence

*5.5 zip(iterables)

We generally think that this method is the inverse process of zip, it is a process of unzip, for example to illustrate its use:

5.6 Complex example

Let’s look at a more complex example

The explanation of this example is:

1. [ x] is a list containing lists, x itself is a list
2. [ x]*3 The result is [x,x,x], which is actually [[4,5,6],[4,5,6],[4,5,6]]
3. [*[ x]*3] The result is [(4,4,4),(5,5,5),(6,6,6)]

5.7 zip usage

The following is a practical example of zip to illustrate its application:

1. List sum

1. Data consolidation

1. Dictionary key-value conversion

For loop implementation:

Use zip to achieve: