Want to learn what Python variables are and what you can do with them? That’s exactly what we’ll cover in this article. Now that you’re at Part 2 of our Python series, it’s time to learn about Python variables. (Yes, Part 2 means there is also a Part 1. For those who missed it, Part 1 discusses Python’s data types and some basic mathematical operations. It also introduces the concept of a function.
This article contains everything you need to know for how to reverse a list in Python. Have you ever wondered how to write a program in Python that checks if a word reads the same backward as forward? Or have you simply wondered how to write your name backward with the help of Python? If your answer is yes to either of these questions, then keep reading. Here, you will learn how to use lists in Python and how to sort or reverse list elements in the desired order.
Want to become proficient with Python operators? In this comprehensive guide, you’ll learn everything you need to know about the types of operators in Python, their differences, and syntax and explore cases with easy-to-follow code examples. What Are Operators in Python? Operators are special symbols used to perform different operations on variables and values. The variable or value that the operator operates on is called the operand. In Python, operators are divided into the following groups:
Everything you need to get started with lists and list comprehension in Python. Here comes the New Year — the perfect time for your own personal re-evaluation and a retrospective of the last year. It’s also a great time to sit down and write a list of New Year's resolutions that you are planning to achieve in the incoming year. Are you going to write it on paper or will you reach for your laptop and, like any other nerd, use Excel or some other tool like Python to save and maintain this list?
Wondering how to get the most out of Python dictionaries? In this comprehensive guide, we’ll cover all you need to know to effectively use dictionaries in your studies and in real-world projects. What Is a Python Dictionary? A Python dictionary is yet another very useful and important data type. Basically, Python dictionaries are an unordered collection of data values. However, in contrast to other data types, a dictionary’s elements are key-value pairs instead of single data values.
Want to learn Python but think you have to know something before you start? You don’t! That’s the whole point of learning, as you’ll see. So you want to learn Python, but something is stopping you. What is it? The usual misconception that stops people from doing something is that they should know everything, even before they start learning. This misconception makes you think everybody was born with their knowledge and that you’re never going to reach their level.
Python provides a lot of libraries to help developers with their work. Which of them will be the most popular in 2020? And which are worth your time? Here are our picks for the 13 top Python libraries. Python is one of the most popular programming languages. Many developers choose Python because it’s easy to learn and good for varied tasks, including data science, machine learning, data analysis and visualization, and web or desktop app development.
Sometimes you need a random number or element. How can Python help? The truth is that randomness is all around us. Think about the lottery, a dice roll, or the (extreme) randomness of your office’s Secret Santa workings. In this article, we'll discuss pseudo-randomness, how it's different from true randomness, and how it can be applied in Python to generate random numbers. We'll also delve into some more advanced topics, like reproducible coding with random numbers and using the choice() and choices() functions to return random string elements from a list.
Both lists and arrays are used to store data in Python. Moreover, both data structures allow indexing, slicing, and iterating. So what’s the difference between an array and a list in Python? In this article, we’ll explain in detail when to use a Python array vs. a list. Python has lots of different data structures with different features and functions. Its built-in data structures include lists, tuples, sets, and dictionaries.
Learn Python, save lives. Yep, you heard me. No, I’m not talking about dragging babies from burning buildings or solving tensions in the Middle East. And no, perhaps you won’t win a slew of civic hero awards anytime soon or collect the keys to the city. But there are certainly some compelling reasons why Python is so popular. Among them are some life-saving applications. In this article, we’ll look at the many and varied uses of Python, the characteristics that make it so incredibly popular, as well as some of the downsides you should be aware of before choosing Python as your new language-learning challenge.
You’re in a hurry! Does your boss want you to finally learn to code? Or would you like to start a career as a programmer? We'll show you how to learn Python fast and how long it will take. I assume you've already decided to become a programmer. You know it's a good opportunity. You browse job postings, and you can't believe how many are on the market. But you don't know which language to learn.
Chances are you’ve heard about the infinite possibilities Python gives you both in your professional and private life. When you sit down at your desk, full of motivation and eagerness, the question that probably comes to your mind is: how long does it take to learn Python? You’ll find the answer here! Professionals around the world love Python. According to IEEE Spectrum, an industry magazine issued by the largest international engineering organization, Python is the most popular programming language (see how others were ranked here).
Want to start learning Python but struggling to find quality resources? Well, they're out there—and we'll review them here. In no particular order, here are the best online resources to learn Python. Courses 1. Vertabelo Academy Vertabelo Academy is an interactive e-learning platform that offers nine Python courses. Among them, you can find two learning paths: programming and data science. Programming path: Python Basics Part 1. This is the first of a two-part course that covers everything you need to know about Python so you can start writing your own scripts and applications.
Python is one of the fastest growing programming languages in the world. It is becoming equally popular among novice and experienced programmers and taking over rival languages such as C++ and Java. One of the biggest reasons why Python's popularity has skyrocketed is its simplicity and flexibility. Even people with no prior programming knowledge can learn Python within weeks. In fact, Python has all the characteristics to become the lingua franca of coding in the near future.
Providing various types of data in a unified way is one of the core concepts of web communication. In recent years, JSON text files have become extremely popular due to their simplicity and universality. Vertabelo Academy’s recent course—How to Read and Write JSON Files in Python—explains how to manipulate JSON files in Python. If you work with Python and want to learn a practical skill in high demand, you’re in the right place.
Do you know the feeling when you’ve read the theory behind some programming concepts but you’re at a loss when it comes to writing actual code? Vertabelo Academy’s new course—Python Data Structures in Practice—addresses this exact problem by explaining the practical aspects of basic data structures. The course discusses frequent use cases and teaches you optimal solutions to common problems. As a bonus, you’ll create a real Python game!
Python can help you get more insights from your data, make better-informed data-driven decisions, automate many routine activities, and increase the ROI from your marketing campaigns. Interested? Then let’s see how exactly Python can boost your marketing efforts. How Can Your Marketing Activities Benefit from Python? As a marketer, you probably face a number of challenges: Ads are getting more expensive. Previously profitable marketing channels, like content marketing, are becoming crowded.
If you have basic knowledge about Python and are looking for an IDE to work with on your own computer, consider the Jupyter Notebook. It is a good tool, especially for Data Science projects. What is Jupyter Notebook? Jupyter Notebook is an open-source server-client application used to create and run mainly Data Science projects. Where does its name come from? JUPYTER is an acronym of Julia, Python, and R, because they were the first programming languages supported by this editor.
The PyCharm IDE is one of the most popular editors used by professional Python developers and programmers. But if you are a beginner, don’t worry, it can help you too! Find out how to create Python projects using PyCharm and what basic features can help you write code more efficiently. The PyCharm IDE is one of the most popular editors used by professional Python developers and programmers.
Python was my love at first sight. It was at the very beginning of my interest in programming when I took my first Python course, and I instantly fell in love with this language. Unfortunately, I had few opportunities to work professionally in the Python environment, but I kept learning after hours, just for fun, until my new job became too demanding and I simply had no more time for my coding hobby.
This tutorial will show you how to install the PyCharm IDE on your own computer–whether you have Windows or Ubuntu. To start developing with the PyCharm IDE, you need to download and install it on your computer’s operating system. PyCharm is an editor developed by the JetBrains company. As of today, it is the most popular IDE used by Python developers. Knowing this, JetBrains delivers PyCharm in three versions: Professional (full-featured IDE), Community (lightweight IDE, not full-featured), and Educational (community IDE with added education features).
Ever wondered how you can use Python to create stunning data visualizations? In the first part of this series, we saw how to draw line plots and histograms using the matplotlib library. We also saw how to change the default size of a plot and how to add titles, axes, and legends to a plot. In this article, we’ll see a few more types of plots that can be drawn using the matplot library with pro tips on how to improve them.
At some point in your Python journey, you’ll definitely need to work with dates, times, or both. Learn all the basics of date and time in Python with this short tutorial. Need to calculate how long it’s been since a given date? Working with date and time objects in Python? In this beginner’s guide, we’ll take a look at how to write programs with these two key data types in Python.
Want to know how Python is used for plotting and data visualization? Interested in learning one of the most commonly used data visualization libraries in Python? If so, you’re in the right place. In this installment of a two-part tutorial, we’ll learn how to use matplotlib, one of the most commonly used data visualization libraries in Python. Over the course of both articles, we’ll create different types of graphs, including:
Even if you’re just starting your Python journey, you’ve most likely come across Python sets. But do you know how to use them effectively? This article aims to cover all the main Python set operations to give you a better feel for when and how to use this important data structure. What Are Python Sets? First, let’s start with the basics. A set is a built-in type in Python that has a number of important characteristics:
Python is one of the most frequently used programming languages for financial data analysis, with plenty of useful libraries and built-in functionality. In this article, you’ll see how Python’s machine learning libraries can be used for customer churn prediction. Customer churn is a financial term that refers to the loss of a client or customer—that is, when a customer ceases to interact with a company or business. Similarly, the churn rate is the rate at which customers or clients are leaving a company within a specific period of time.
You already have some foundational knowledge of Python for data science. But do you write your code efficiently? Check out these tips and tricks to supercharge your Python skills. How to Write Efficient Python Code In this article, we’ll take a look at some tricks that will help you write fast and efficient Python code. I’ll start with how to optimize code that involves the pandas library. If you want to refresh your knowledge of pandas, check out our Introduction to Python for Data Science course.
Another Python course is now available on Vertabelo Academy. “How to Read and Write CSV Files in Python” is an online course for anyone interested in working with files in Python—a must-have skill for any beginner software developer or data scientist! After the great success of our SQL courses, we began working hard on the Python learning path. So far, we’ve made five Python courses available, and we’re proud to announce the release of yet another one: How to Read and Write CSV Files in Python!
How can Python’s pandas library be used to analyze time series data? Let’s find out. The pandas library is frequently used to import, manage, and analyze datasets in a variety of formats. In this article, we’ll use it to analyze Microsoft’s stock prices for previous years. We’ll also see how to perform basic tasks, such as time resampling and time shifting, with pandas. What is Time Series Data? Time series data contains values dependent on some sort of time unit.
One of the most popular Python IDEs is Spyder, which stands for Scientific PYthon Development EnviRonment. This Python tool is “designed by and for scientists, engineers and data analysts.” But it’s not just for professionals. In this article, we’ll learn why the Spyder IDE is also an excellent tool for beginners. In this article, I’ll: Show you how to install Spyder on Windows and Linux. Guide you in starting a project and creating your first Python script.
Regression analysis is one of the most fundamental tasks in data-oriented industries. In simple words, it involves finding a relationship between independent and dependent variables (attributes) in a given dataset. Consider the example of a house price prediction problem—given the size and number of bedrooms, we want to predict the price of a house. This is a simple regression problem where the size of the house and the number of bedrooms are the independent variables and the price of the house is the dependent variable.
You’ve spent hours studying Python, and you may even have several successful projects in your portfolio. But do you write your Python code like a pro? Let’s review some important guidelines to help you clean up your code. What Is the Pythonic Way of Writing Code? There are often several ways to do something in Python; naturally, some are better than others. But you should always prefer code that is not only syntactically correct but also in alignment with coding best practices and the way the language ought to be used.
Online Python courses help you acquire basic knowledge of working with Python. But how do you retain what you’ve learned and start writing Python code on your own? Nowadays, there are plenty of e-learning platforms for programming languages like Python. With these platforms, you can learn the fundamentals of the Python language: syntax, basic functions, and programming best practices. On platforms like Vertabelo Academy, for example, you don’t need others tools to work through the content and can get your hands dirty with a language in a sandbox environment.
If you have just started learning Python, now is a great time to develop your skills further. Nowadays it is not problem to find resources about Python on the internet, however, it can be difficult to find good materials to read for beginners. Therefore I decided to gather and share with you my “Lucky thirteen” articles on Python written in 2018. Top 3 Vertabelo Academy Python Articles for Beginners The Vertabelo Academy is an online learning platform that delivers courses on SQL, data science, and Python.
Python is a simple yet powerful programming language that’s a must for beginners and advanced programmers alike. Here’s why. High-level programming languages have one goal in mind: to make your life as a programmer easier. Messy syntax and obscure keywords? Forget about it. With languages like Python, you can get away with understanding just the basics of programming, enough to begin writing your own scripts and apps. And since Python developers are high in demand, Python is a great language to learn if you want to pursue a career in software development or big data.
In this comprehensive beginner’s guide, we’ll look at how to install Python on three major operating systems, choose a Python IDE, and run your code. Would you like to start coding in Python but don’t know where to begin? Maybe you’ve graduated from an online course like Python Basics and now are looking to continue your Python adventure on your own machine. But first, why Python? The answer is simple: Python is a very easy-to-learn and powerful programming language.
An increasing number of fintech companies are using Python for data analysis. But what makes Python so special? And why is it a better language for data analysis compared to traditional software? Python is quickly becoming the most popular coding language in the world. Currently, it’s perching comfortably in the fourth spot after Java, C, and C++ on the Tiobe Index of Language Popularity. And the Popularity of Programming Language Index ranks Python as the most popular programming language in the world in October 2018.
Python is a programming language frequently used by scientists and data analysts to build applications. Why? Because it’s easy to use and has few rules. But simply installing Python isn’t enough—you also need a good interactive development environment (IDE) to program in. So what are the best Python IDEs for data science? Let’s find out! (Note: all IDEs presented here support Windows, macOS, and Linux.) 1. Enthought Canopy Enthought Canopy is one of the best Python IDEs for scientists and engineers.
Heat maps are a great way to visualize patterns in data, but some businesses avoid them because creating them seems challenging and time consuming. Well, it’s not. Do you know what the most popular programming language currently is? According to the PYPL Index, it’s—you guessed it—Python. And our serpentine friend was also crowned the best programming language in 2018 by Linux Journal readers. Why all the buzz? Because Python is simple and easy to learn.
Information technology is one of the hottest industries in the world and offers thousands of job in each major city around the globe. If you’re a student or professional who wants to get IT skills and find your first job in the industry, Vertabelo Academy can help you get started. The range of IT jobs available is stunning—from software engineers to system administrators and data scientists, IT rules the job market.
The Vertabelo Academy Team has been working hard to release a brand-new course, and it’s finally here! Python Basics for Programming is a great place to start for anyone aspiring to become a software developer. Since our SQL courses, the Vertabelo Academy platform has been embraced by thousands of students who are eager to learn new technologies. After releasing Intro to Python for Data Science last month, we asked ourselves: why not create another introductory Python course, but this time from a software developer’s perspective?
One of the oldest jokes in the business world goes like this: The CFO asked the CEO, “What happens if we invest in developing people and they leave us?” The CEO answered, “What happens if we don’t and they stay?” If you’re like the CEO and want to help your employees grow, this article will explain how you can do so with Vertabelo Academy. Vertabelo Academy has been around since 2015.
Over the past three months, we’ve been working on something completely new. Please welcome our new course on Python data analysis! We got many emails from users like you with good feedback on our Introduction to R course. So first, I want to start off with a big thank you—reading your wonderful comments was like a burst of energy! We’re always looking to improve our offerings, and we greatly value your input.
R and Python are two of the most popular data science languages, but which one is better? And will Python replace R in the near future? Let’s find out! R vs. Python: the Basics First, some history. R first appeared in 1990; it was derived from the language S, a statistical programming language developed for statisticians. It was (and still is) commonly used in educational settings and is a favorite among biostatisticians.