Seaborn Library for Data Visualization in Python: Part 1

Introduction In the previous article, we looked at how Python’s Matplotlib library can be used for data visualization. In this article we will look at Seaborn which is another extremely useful library for data visualization in Python. The Seaborn library is built on top of Matplotlib and offers many advanced data visualization capabilities. Though, the Seaborn library can be used to draw a variety of charts such as matrix plots, grid plots, regression plots etc., in this article we will […]

Read more

Sets in Python

Introduction In Python, a set is a data structure that stores unordered items. The set items are also unindexed. Like a list, a set allows the addition and removal of elements. However, there are a few unique characteristics that define a set and separate it from other data structures: A set does not hold duplicate items. The elements of the set are immutable, that is, they cannot be changed, but the set itself is mutable, that is, it can be […]

Read more

Seaborn Library for Data Visualization in Python: Part 2

In the previous article Seaborn Library for Data Visualization in Python: Part 1, we looked at how the Seaborn Library is used to plot distributional and categorial plots. In this article we will continue our discussion and will see some of the other functionalities offered by Seaborn to draw different types of plots. We will start our discussion with Matrix Plots. Matrix Plots Matrix plots are the type of plots that show data in the form of rows and columns. […]

Read more

Building a GraphQL API with Django

Introduction Web APIs are the engines that power most of our applications today. For many years REST has been the dominant architecture for APIs, but in this article we will explore GraphQL. With REST APIs, you generally create URLs for every object of data that’s accessible. Let’s say we’re building a REST API for movies – we’ll have URLs for the movies themselves, actors, awards, directors, producers… it’s already getting unwieldy! This could mean a lot of requests for one […]

Read more

Introduction to Web Scraping with Python

Introduction Web-scraping is an important technique, frequently employed in a lot of different contexts, especially data science and data mining. Python is largely considered the go-to language for web-scraping, the reason being the batteries-included nature of Python. With Python, you can create a simple scraping script in about 15 minutes and in under 100 lines of code. So regardless of usage, web-scraping is a skill that every Python programmer must have under his belt. Before we start getting hands-on, we […]

Read more

Pandas Library for Data Visualization in Python

In my previous article, I explained how the Seaborn Library can be used for advanced data visualization in Python. Seaborn is an excellent library and I always prefer to work with it, however, it is a bit of an advanced library and needs a bit of time and practice to get used to. In this article, we will see how Pandas, which is another very useful Python library, can be used for data visualization in Python. Pandas is primarily used […]

Read more

Python Logging Basics

Introduction Logging helps you keep track of events happening during the execution of your code, which can then be used in the future for debugging purposes. It provides a better picture of the flow of the application and helps developers trace the source of errors that happens during execution of your code, thereby enhancing the maintainability of the application. In Python, most of the basic logging features are provided by the Python standard library. Hence, you can add logging to […]

Read more

Python Nested Functions

What is a Nested Function? Functions are one of the “first-class citizens” of Python, which means that functions are at the same level as other Python objects like integers, strings, modules, etc. They can be created and destroyed dynamically, passed to other functions, returned as values, etc. Python supports the concept of a “nested function” or “inner function”, which is simply a function defined inside another function. In the rest of the article, we will use the word “inner function” […]

Read more

Intro to the Python Random Module

Introduction Even for someone not interested in computer programming, the usefulness of generating random numbers in certain circumstances is something obvious. In most board games we throw dice to generate an unpredictable number that defines the player’s next move. Also, we can all agree that playing any card game would be pointless without a proper shuffle between rounds. But random numbers are not only important in relatively trivial fields like entertainment or gambling. They’re especially crucial in the field of […]

Read more

Using Plotly Library for Interactive Data Visualization in Python

In my previous article, I explained how the Pandas library can be used for plotting basic and time series plots. While Pandas, Matplotlib, and Seaborn libraries are excellent data plotting libraries, they can only plot static graphs. Static plots are like simple non-interactive images. In most of the cases, static plots are enough to convey the information. However, in some cases you may like to add user interactivity to your plots. In this article, we will see how the Python’s […]

Read more
1 805 806 807 808 809 856