Python is the great language for beginners which are easy to learn and maintain. To start programming in python, it’s easy to complete a program within two days. By using other languages it is extremely vast because in that go into its packages, like its machine learning packages, SciPy packages, Matplotlib and so on. So, it might take more time to complete.
- Python’s biggest strength is that its bulk of library is portable.
- There are millions of people around the world are working on Python and making contributions to its development.
- It’s an open-source language. If you have Python in your system means write your own piece of package and then submit it for approval.
- There are hundreds and thousands of packages available that are portable and helps in programming to clarify some of the stuff.
It is a GUI-based development environment having the Python packages connected to Python. For example, everyone has Twitter and Facebook accounts. How do analyze date from Twitter and Facebook? PyCharm package is used 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 worked hard in order to create these packages. Accordingly, 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 it by writing 50-60 lines of code.
Machine learning algorithms are mostly used to create artificial intelligence in machines which are also available in SciKit Learn. It has been optimized in a way that the machine learning code would write in just 4-5 lines. Use this package, invoke those procedures and functions, pass the data, fit your model and then predict the outcome which is very easy. Python has made 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.
With libraries like PyDoop and SciPy, it’s a dream come true for Big Data Analytics. Nowadays, there are tons of data flowing from everywhere, those would be analyzed first. In some organizations, they have the data from the past 70 years, while in others they have data from past 30-40 years and it’s too huge. They would store 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’s are important in a way. It’s not just important, it’s necessary to find a trend.
For example, 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 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. 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. Nowadays, we can process the data for 30 years and find a pattern, which might be anything. It should be sin wave or cosine wave to some graph, which is not any kind of wave, but just a zigzag graph which tell the pattern. In order to implement those algorithms with so much of data with the help of libraries like, PyDoop and SciPy.
Growing Interest in Python
Last 30 years the python has been there, but the growth of interest started in July, 2010. The name python is originated from the play in London (UK) doesn’t derive from the animal python (snake). In July 2010 the interest of Python started growing well to today itself. Most of the organizations, particularly the one dealing with data and Data Analytics asking the experienced and also having knowledgeable person in python.
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