The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

Related:

Who Are the Main Players in Big Data?

The short answer is, yes and no. It depends upon who you are. The purpose of this entry is to help you determine, yes or no.

Full disclosure. This entry is created on a Mac mini. And doing so on Windows 8 (Release Preview). If you are a developer, in my humble opinion you need to test on all platforms you expect your app to run or you are not much of a developer.

To be successful you need to leave politics in geographical territory known as Washington DC. My definition of that is: 14 mi.² of real estate surrounded by reality.

Only in politics can we afford to take sides. Those of us in IT, especially developers need to do our best to be all things to all people. Certainly this is a technical impossibility. However in our game we can get some points for at least being serviceable if not outstanding.

Python is an incredibly powerful and useful computer programming language that many of the biggest websites in the world rely on for their foundation. Python provides reliable results that are functional and involve a variety of dynamic scripted and non-scripted contexts. And because it is free and open source, it has remained a popular choice for a variety of different developers who are looking to build new sites on one of the most reliable languages available. Here is a look at 10 of the most famous software programs that are written in Python and what they do.

YouTube
If you love watching hours of homemade and professional quality video clips on YouTube, you can thank Python for giving you that option. The foundation for Python helped YouTube integrate streaming videos into their pages, as well as the ability to like videos and embed certain information. YouTube is one of the most popular sites on the Internet, and it runs off of one of the most powerful languages in Python.

DropBox
What started as a powerful app, DropBox is now used by a variety of individuals, businesses, companies, organizations and more. This program lets you save files to a cloud-based service, that you can then access from anywhere in the world. With Python at the root of DropBox, there is no longer a need for USB sticks or blank CDs, since you can now save and share everything with your cloud-based account.

Google
It takes a lot of power to be able to handle the most popular search engine in the entire world. That is why Google uses Python for its mainframe foundation, as well as in addition to various apps that it runs in conjunction with the main site. The ease that Google provides for finding certain information, would be impossible without Python at the core.

Quora
Got a question? Ask it on Quora. This site compiles a list of questions and answers that come from a community of individuals. Those questions are then organized by various members of the community, which puts the most relevant information at the top. The creators of Quora, who happened to be former Facebook employees, decided to use Python to help them create the world’s best Magic 8 ball in Quora.

Instagram
If you love taking photos of your food or a new outfit and posting it online for all of your friends to see, you can thank Python for that ability. Granted, Instagram has both a very powerful app and a website, but the latter runs on Python language. The system allows for users to browse, find and post pictures that they like on the site.

BitTorrent
BitTorrent has evolved quite a bit in recent years, but its foundation and earlier years were built on Python. When it comes to one of the largest databases of knowledge, media and content, BitTorrent is the way to go. But you wouldn’t be able to get any of those lectures or other legal stuff that you are downloading from BitTorrent, if it wasn’t for Python.

Spotify
Spotify changed the music game when it allowed you to listen to ad-free music of your choice. This wasn’t a program where you got to select a playlist, but rather full songs that you love, on repeat as many times as you can imagine, if you so desire. But whether you are rocking out to the latest K-Pop song from Psy or a classic jazz tune, you are doing so because Spotify was built on Python.

Reddit
Reddit is one of the biggest open communities on the web. You have a question, want to talk about something in specific, or find tons of information regarding a particular topic, you can just look on Reddit. The site relies on Python to help them store user names, categorize subreddits, upload links to GIFs and, of course, award gold to valued posters.

Yahoo Maps
Much like Google, Yahoo also uses Python for a variety of different resources. Most valued may be Yahoo Maps. The API and programming behind the maps program, which is built with Python, allows for users to find locations, get directions and even find reviews about local places.

Hipmunk
If you love to travel, you have likely come across Hipmunk. And while the site lets you save money on booking your itinerary through Hipmunk, it is Python that keeps everything organized. Python also helps sort the best discounts and rates, so you can get the best packages available.

Python is an incredibly powerful tool for web development. More and more sites rely on it, including 10 of the most powerful sites in the world that are listed here.

Related:

Current Active List of Organizations that use Python 

Working With Lists In Python

Recently, the new iOS update had added Reminders to the iPhone. If you ever found yourself setting notes on your iPhone to remember to do things, such as buying milk while at the grocery store, this process has become leagues upon leagues simpler, and faster. On your iPhone is an application named “Reminders”. Tap on this application and experience the new world of To-Do lists.

Right away, you are greeted by a screen that looks similar to a notepad, where you would be scribbling down reminders for this, and for that. To start off, tap on the plus button, and you are able to input the reminder you want. Say you want to be reminded to “Buy Milk.” Just type that into the application and you’re good to go.

But wait, there’s more. What this new application brings to the table that is extremely useful is the fact that your iPhone can remind you to do that task at a certain location, which, in this case, is buying milk. If you had saved your regular grocery store in your Maps application as a favorite location, you are able to do so. (To save a favorite location, go into your Maps application, search for your nearest grocery store that you regularly shop at, tap on the pin, tap on the blue arrow to get more information, and “Add to Bookmarks.”) In order to remind you to buy milk at your favorite grocery store, slide the “Off” to “On” and you are now able to set where you would like to be reminded at, and at what point in time. Now, you will never leave the grocery store without buying milk!