Data Analytical languages or as they are popularly known, programming languages tend to be a little on the difficult side when it comes to learning them. Of all of them, it is believed that Python is one such language or tool, which is pretty easy to learn, especially when we compare it to the others. The syntax that this programming environment provides is not really that ceremonial and is quite easy to get a hang of. This helps all of those non-programmers work really efficiently in this software. When it comes to learning python or teaching it to someone, it is easier to do so with examples as opposed to teaching say Ruby or Perl mainly because of the lesser number of rules and special cases that Python has.
Many might have heard this name ‘Python’ for the very first time in the past couple of years. But what is interesting to know that this programming language has existed in the industry for the past 27 years, which is a lot more time. What then makes this tool so relevant in spite of being so old? It is the fact that Python can be pretty much applied to any and every software development or operations scenario that you can find in the world today. You can make use of python if you are looking to manage local and cloud infrastructure, or developing websites or have to work with SQL or even if you are looking for a custom function in order to make do with Pig or Hive, then Python applies there as well, this is a major reason as to why professionals especially those working in the analytical fields must learn python.
With python it is so easy that once you learn the language, you can very easily leverage the platform. It happens to be backed by PyPi which is pronounced as Pie Pie. Herein a user can make use of more than 85,000 modules as well as scripts. These modules are formulated in such a way that they are able to deliver pre-packaged functionality to any of the local python environments as well as solve a number of problems like the working of databases and the glitches therein, implementation of computer vision, and execution of advanced data analytics such as sentiment analysis or building of RESTful web services.
These days it has become quite a norm that any job you happen to be looking for, you will most probably be in need of having a skillset that is defined by big data and analytics which is why it becomes quite important for one to thoroughly understand the working of Python. As this data analytical tool happens to be a strong presence in the various areas of coding as well as data analytics it is sure to rule the roost in the near future. This is why we see a lot of professionals opting to learn Python from various professional training institutes like Imarticus Learning.
