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Why Should you go for Python?

Last updated on Jul 04,2019 1K Views


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Python is a great language for beginners since it’s easy-to-learn and easy-to-maintain. A Python statement is as simple as: print ‘Hello World’. Writing four lines of code with syntax is not required for this. To start programming, you will need only two days to be able to write a program in Python; it’s that easy. It is extremely vast if you go into its packages, like its machine learning packages, SciPy packages, Matplotlib and so on. So, it might take you years to master it, but to start with, it will not take you more than two days.

  • Python’s biggest strength is that its bulk of library is portable.
  • There are thousands of millions of people around the world working on Python and also making contributions to its development.
  • It’s an open-source language. Even you can have Python in your system and write your own piece of package and then submit it for approval. They will see whether it’s good enough, and if it is, they will include your package as well.
  • There are hundreds and thousands of packages available, which are portable. It really helps you in programming some of the stuff.


It is a GUI-based development environment and one of the Python packages, which connect to Python. For example, almost everyone has Twitter and Facebook accounts. How do you analyse date from Twitter and Facebook? PyCharm is the package available, if you want to:

  • pull streaming data from Twitter or Facebook,
  • save it and conduct a search in it,
  • do a sentiment analysis, or
  • run some kind of machine learning algorithm on it.

Many people have worked very hard in order to create these packages. Interestingly, all you have to do is read a little bit of documentation about this package and start implementing, instead of writing thousands of lines of code. Even in Python, you may end up writing 50-60 lines of code.

Machine Learning

Machine learning algorithms are mostly used to create artificial intelligence in machines. Those algorithms are also readily available in SciKit Learn. It has been optimized in a way that you can write your machine learning code in just 4-5 lines. You can use this package, invoke those procedures and functions, pass your data, fit your model and then predict the outcome. It is as easy as that. Python has made a lot of things easier and it is still being contributed by thousands of developers across the world. It’s going to get much better and that is why it’s becoming popular also.

Data Analytics

With libraries like PyDoop and SciPy, it’s a dream come true for Big Data Analytics. In this era, when you have tons of data flowing from everywhere, you first want those data to be analysed. In some organizations, they have data from the past 70 years, while in others they have data from past 30-40 years and it is too huge. They would have stored this data in some database somewhere, and it might be lost. Let’s take data of 1970s; but who cares about the 1970s data in this age? However, to find a trend, those data are important in a way. It’s not just important, it’s necessary to find a trend.

Let’s say, I am in a computer manufacturing company and I want to find a trend as to what’s happening. You might have heard about forecasting and how people do that. Basically, they capture the data of the past 2-3 years. Let’s say, last year in March, the sales were 1 million, in April the number was 2 million, in May 3 million, and so on and so forth. They would just take this data and then extrapolate it to this year. Then, they can assume that since last year in August, it was 1 million, this year too in August, it might be 1 million. That’s how they extrapolate it. There is still more to this algorithm, but this is just a simple example. So just look at the amount of data taken. May be in a couple of years when they average out the data of those years, they may do a moving average or use some kind of statistical algorithm but with a limited amount of data.

With the advent of Hadoop and Big Data, Data Processing has changed. We can now process the data for 30 years and find a pattern, which might be anything. It can be sin wave or cosine wave to some graph, which is not any kind of wave, but just a zigzag graph. Even that can tell you a pattern. Now, in order to implement those algorithms with so much of data you have libraries like, PyDoop and SciPy.

Growing Interest in Python

Python has been there for the last 30 years, but the growth of interest started in July, 2010. Python has not derived its name from the animal, python (snake). It was rather the name of a play in London, UK, where it originated. It was there for a long time, but in July, 2010 the interest in Python started growing and as of today it is growing really well. Most of the organizations, especially the ones dealing with data and Data Analytics ask if you have experience with Python. Even if you do not have any experience, they tend to ask if you know what Python is.

Got a question for us? Please mention them in the comments section and we will get back to you.

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