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.

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Jeff Nelson, a former Googler and inventor of Chromebook says on Quora, “One habit I've clung to is writing small prototypes when I'm trying to learn new concepts.
For example, I'll sit down with a book or a web page, and over the course of a few hours, write 30 or 40 programs all of them only a few dozen lines long.  Each program intended to demonstrate some simple concept. This prototyping makes it very easy to try out many concepts in a short period of time.”

Miguel Paraz, Software Engineering Student habit is to “keep a log in a text file or document on my work computer. Before trying to solve a problem, I write it down first. And then I describe the details as they happen.”

A string in Python is enclosed in either single or double quotes.  Therefore, either one does the trick.  A common practice is to place single words with no characters that can be interpolated in single quotes and multi-word strings that contain interpolated characters in double quotes.  This may be a carry over from Perl where interpolated characters are in double quotes. 

If you do not want to interpolate a string, use a raw string ... r"\n".  With the exception of the last print statement, each of the print statements prints hello on a separate line from how are you?.  They are great for regular expressions.

Finally, triple double quotes """ some message about a function or class ... """ are used for docstrings.

print "hello \n how are you?"
print 'hello \n how are you?'
print r"hello \n how are you?"

JAVA SCRIPT TUTORIAL – THE ESSENTIAL ELEMENTS

If you are looking to increase your proficiency in programming, it can make a lot of sense to invest some time into learning how to use JavaScript, or taking a Java Script tutorial.  It is one of the most popular and powerful options available today for people to use in programming different parts of their websites.  It often finds use in headers, or in interactive features displayed on pages.  It allows you to execute many different functions, such as calculation, pulling data from forms, special graphical effects, customized selections, custom security protocol and password systems, and much more.  Here are some essential points to keep in mind:

·         Java vs. JavaScript – These two languages are not the same.  Java uses completely separate files for their headers and classes, and they need compilation prior to execution.  Java is used in the creation of applets for pages.  JavaScript is much easier and simpler to learn than regular Java, and Java Script tutorials are often significantly more accessible for the average user.

·         OOP – OOP, or object oriented programming, is a specific programming technique that simplifies complicated computer programming conceptual issues.  Essentially, it lets a programmer treat whole chunks of data (defined either by users, or by the system itself), and modify or access them in specific ways.  It does this by classifying different parts of the programming into Objects, Methods, and Properties, which will be discussed more in depth in the future, in other Java Script Tutorials.