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?

As someone who works in many facets of the music industry, I used to seethe with a mixture of anger and jealousy when I would hear people in more “traditional” goods-based industries argue in favor of music content-based piracy. They made all the classic talking points, like “I wouldn’t spend money on this artist normally, and maybe if I like it I’ll spend money on them when they come to town” (which never happened), or “artists are rich and I’m poor, they don’t need my money” (rarely the case), or the worst, “if it were fairly priced and worth paying for, I’d buy it” (not true).  I always wondered if they’d have the same attitude if 63% of the things acquired by customers in their industries weren’t actually paid for, as was conservatively estimated as the case for the music industry in 2009 (other estimations put the figure of pirated music at 95%). Well, we may soon see the answer to curiosities like that. Though one can say with tentative confidence that music piracy is on the decline thanks to services like Spotify and Rdio, it could be looming on the horizon for the entire global, physical supply chain. Yes, I’m talking about 3d printers.

Before I get into the heart of this article, let me take a moment to make one thing clear: I think these machines are incredible. It’s damn near inspiring to think of even a few of their potentially world-changing applications: affordable, perfectly fit prosthetic limbs for wounded servicemen and women; the ability to create a piece of machinery on the spot instead of having to wait for a spare to arrive in the mail, or en route if your car or ship breaks down in a far away place; a company based out of Austin, TX even made a fully functioning firearm from a 3d printer a few months ago.

If these machines become as consumer-friendly and idiot-proof as possible (like computers), it’s possible that in a matter of decades (maybe less), a majority of U.S. households will have their own 3d printer. There’s also the possibility they could take the tech-hobbyist path, one that is much less appealing to the masses. Dale Dougherty of Makezine.com estimates there are currently around 100,000 “personal” 3d printers, or those not owned for business or educational purposes. I don’t think they’ll ever be as ubiquitous as computers, but there are plenty of mechanically inclined, crafty hobbyists out there who would love to play around with a 3d printer if it was affordable enough.

That being said, is there reason to worry about the economic implications of consumers making what they want, essentially for free, instead of paying someone else to produce it? Or will the printers instead be used for unique items more so than replicating and ripping off other companies’ merchandise in mass amounts? The number of people working in industries that would be affected by a development like this is far greater than the number of people who work in content-based industries, so any downturn would probably have a much larger economic implications. Certainly, those times are a ways off, but a little foresightedness never hurt anyone!

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

Anonymous reprint from Quora (career advice)

Occasionally we come across a unique profound perspective that makes one stop and really listen. The following advice is one such as this.

1. Small actions compound: Reputation, career trajectory, and how others perceive you in the workplace can come down to a handful of things/moments that seem inconsequential/small at the time but compound. Random Thought: Redwood trees come from small seeds and time. With every action you're planting small seeds and these seeds can grow into something bigger (sometimes unimaginably bigger) over time. Don't let small basic mistakes sabotage your reputation because it only takes a few small snafus for people to lose confidence/trust in your ability to do more important tasks. Trust is a fragile thing and the sooner people can trust you the faster they'll give you more responsibility. Some Examples: Being on time (always) or early (better); spending an extra 10-15 minutes reviewing your work and catching basic mistakes before your boss does; structuring your work so it's easy for others to understand and leverage (good structure/footnotes/formatting); taking on unpleasant schleps/tasks (volunteer for them; don't complain; do it even when there's no apparent benefit to you)  


2. Rising tide lifts all boats: Fact: You don't become CEO of a multi-billion dollar public company in your 30s based purely on ability/talent. Your career is a boat and it is at the mercy of tides. No matter how talented you are it's a lot harder to break out in a sluggish situation/hierarchy/economy than a go-go environment. Even if you're a superstar at Sluggish Co., your upside trajectory (more often than not) is fractional to what an average/below average employee achieves at Rocket Ship Co. There's a reason Eric Schmidt told Sheryl Sandberg to "Get on a Rocket Ship". I had colleagues accelerate their careers/income/title/responsibility simply because business demand was nose bleed high (go go economy) and they were at the right place at the right time to ride the wave. Contrast that to the 2008 bust where earnings/promotions/careers have been clamped down and people are thankful for having jobs let alone moving up. Yes talent still matters but I think people generally overweight individual talent and underweight economics when evaluating/explaining their career successes. Sheryl Sandberg Quote: When companies are growing quickly and they are having a lot of impact, careers take care of themselves. And when companies aren’t growing quickly or their missions don’t matter as much, that’s when stagnation and politics come in. If you’re offered a seat on a rocket ship, don’t ask what seat. Just get on.


3. Seek opportunities where the outcome is success or failure. Nothing in between! You don't become a star doing your job. You become a star making things happen. I was once told early in my career that you learn the most in 1) rapidly growing organizations or 2) failing organizations.  I've been in both kinds of situations and wholeheartedly agree. Repeat. Get on a rocket ship. It'll either blow up or put you in orbit. Either way you'll learn a ton in a short amount of time. Put another way; seek jobs where you can get 5-10 years of work experience in 1-2 years.


4. Career Tracks & Meritocracies don't exist: Your career is not a linear, clearly defined trajectory.  It will be messy and will move more like a step function.


5. You will probably have champions and detractors on day 1: One interesting byproduct of the recruiting & hiring process of most organizations is it can create champions & detractors before you even start the job. Some folks might not like how you were brought into the organization (they might have even protested your hiring) and gun for you at every turn while others will give you the benefit of the doubt (even when you don't deserve one) because they stuck their neck out to hire you. We're all susceptible to these biases and few people truly evaluate/treat folks on a blank slate.


6. You'll only be known for a few things. Make those labels count: People rely on labels as quick filters. Keep this in mind when you pick an industry/company/job role/school because it can serve as an anchor or elevator in the future. It's unfortunate but that's the way it is. You should always be aware of what your "labels" are.


7. Nurture & protect your network and your network will nurture & protect you: Pay it forward and help people. Your network will be one of the biggest drivers of your success.