Lists are one of the most powerful data types in Python. In this Python List Tutorial, you’ll learn how to work with lists while analyzing data about mobile apps. In this tutorial, we assume you know the very fundamentals of Python, including working with strings, integers, and floats.
#python list #python
Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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When we’re programming in R (or any other language, for that matter), we often want to control when and how particular parts of our code are executed. We can do that using control structures like if-else statements, for loops, and while loops.
Control structures are blocks of code that determine how other sections of code are executed based on specified parameters. You can think of these as a bit like the instructions a parent might give a child before leaving the house:
“If I’m not home by 8pm, make yourself dinner.”
Control structures set a condition and tell R what to do when that condition is met or not met. And unlike some kids, R will always do what we tell it to! You can learn more about control structures in the R documentation if you would like.
In this tutorial, we assume you’re familiar with basic data structures, and arithmetic operations in R.
Not quite there yet? Check out our Introductory R Programming course that’s part of our Data Analyst in R path. It’s free to start learning, there are no prerequisites, and there’s nothing to install — you can start learning in your browser right now.
Start learning R today with our Introduction to R course — no credit card required!
(This tutorial is based on our intermediate R programming course, so check that out as well! It’s interactive and will allow you to write and run code right in your browser.)
In order to use control structures, we need to create statements that will turn out to be either
FALSE. In the kids example above, the statement “It’s 8pm. Are my parents home yet?” yields
TRUE (“Yes”) or
FALSE (“No”). In R, the most fundamental way to evaluate something as
FALSE is through comparison operators.
Below are six essential comparison operators for working with control structures in R:
==means equality. The statement
x == aframed as a question means “Does the value of
xequal the value of
!=means “not equal”. The statement
x == bmeans “Does the value of
xnot equal the value of
<means “less than”. The statement
x < cmeans “Is the value of
xless than the value of
<=means “less than or equal”. The statement
x <= dmeans “Is the value of
xless or equal to the value of
>means “greater than”. The statement
x >e means “Is the value of
xgreater than the value of
>=means “greater than or equal”. The statement
x >= fmeans “Is the value of
xgreater than or equal to the value of
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Python lists are a built-in type of data used to store items of any data type such as strings, integers, booleans, or any sort of objects, into a single variable.
Lists are created by enclosing one or multiple arbitrary comma-separated objects between square brackets.
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List comprehension is used for creating lists based on iterables. It can also be described as representing for and if loops with a simpler and more appealing syntax. List comprehensions are relatively faster than for loops.
The syntax of a list comprehension is actually easy to understand. However, when it comes to complex and nested operations, it might get a little tricky to figure out how to structure a list comprehension.
In such cases, writing the loop version first makes it easier to write the code for the list comprehension. We will go over several examples that demonstrate how to convert a loop-wise syntax to a list comprehension.
Basic structure of list comprehension (image by author)
Let’s start with a simple example. We have a list of 5 integers and want to create a list that contains the squares of each item. Following is the for loop that performs this operation.
lst_a = [1, 2, 3, 4, 5] lst_b =  for i in lst_a: lst_b.append(i**2) print(lst_b) [1, 4, 9, 16, 25]
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