Never before has the ‘Data’ been regarded as a highly valuable commodity as it is now. We presently generate 2.5 Quintillion bytes of data per day. One would be able to comprehend the behemoth size of this number by realizing the fact that 90 percent of the existing worldwide data has been created in the past two years. Of course, to leverage the rapidly growing $189 Billion Global data industry, certain specialized tools are required. In this case, we are taking about Python as a programming tool in the field of Data Science.
If you are looking to make a career as a Data Science professional, then you might consider learning Python from a Reputable Institute like PST Analytics. It will surely help you kick start a rapidly growing career in this field.
Go ahead and read this post to find out the reasons as to why Python is preferred over other Data Science tools.
Let us get started!
Python Simplifies Data Science
There are many tools at the disposal of Data Science professionals. However, Python outruns them in most aspects. Python’s features and relatively efficient and light code makes it a preferred tool for processing large data sets. For example, Python is compatible with Hadoop because of its parallel processing capabilities. One can easily write MapReduce programs to process data extracted from the HDFS Cluster. Moreover, Python sports a plethora of libraries like Pydoop, Pyspark, Dask, etc. that keeps the coders from writing lengthy complex codes.
Another crucial application of Data science is in Machine Learning that ultimately is the driving factor behind Artificial Intelligence. Python, for example makes ML a breeze with Reinforcement learning with tools like Open AI, Keras, TensorFlow etc. It also enables Deep learning for smart AI systems without making the code too complex.
Python’s Learning Curve is Easier
It can become tiring to identify open or close curly braces within the code if one is using a traditional language like C++ or Java. Also, a person can be very good with numbers but not with coding. Python address these gaps for the beginner Data Science professionals. Firstly, Python resembles the English language which makes it familiar to the person. Secondly, it has a large support community over the world and a package index with 1,30,000+ projects to serve any programming need. A beginner Data Scientist/Analyst can expect himself/herself to start using Python in daily life within a few days of training from a reputed training institute.
It Comes with Powerful Packages
Python comes with an array of Packages that are nothing but a collection of codes and scripts that can be used for any Data science or analytics need. Some of the highly useful packages that have made Python popular are;
- Pandas- A popular data analytics library that comes with Python. It offers a vast range of functions to manipulate the data present in table format or time series.
- Scipy- A library for Scientific Computing that is often used in Data Science and Engineering. Scipy library allows the user to perform mathematical operations like Interpolation, Linear Algebra, Image processing, FFT, etc.
- Tensorflow- A renowned and heavily used Machine Learning library that was developed by Google to enable research in Deep Neural Networks. With a single API, Tensorflow allows the user to compute data/perform operations across multiple CPUs and GPUs.
- PyBrain- This is Python’s AI and Neural Network Library. This library offers the user with powerful, yet simple and efficient ML Algorithms. It also allows the user to test and compare different algorithms within different environments.
It allows for Data Visualization
Data Visualization is the buzzword for businesses as of now and it is powering modern day enterprises with informed decisions. Data Visualization is nothing but representation of numbers and the correlations between them as graphics for easier interpretation. Though, there is a debate as to whether ‘R’ or ‘Python’ is better for programming, Python certainly has improved its Data Visualization game in the past years. With new libraries like ggplot, Matplotlib, Pygal, NetworkX, etc. and API like Plotly, this language is becoming a popular choice for Visualizing Data.
Python is Versatile
Python has been labelled as a versatile tool by the programming community across the globe. Python is a one-stop solution for Developers and is bound to grow manifolds in the coming years. It is employed with equal suitability for AI, ML, Big Data, Web Development, etc. Moreover, Python is the first choice of people for DIY Projects, Startups, Medium Sized Companies and Giant corporates alike. Its code is simple to compile, analyze and scale. The code is also lightweight and highly scalable. Another highly useful aspect of this language is its ability to ‘Automate.’ Python is the most preferred language for automating simple or complex computing operations. Python allows you to run ‘Scripts’ which are collections of codes that can check themselves for Runtime errors.
Do you think Python should be a top priority in your Career growth manifesto? Let us know in the comments below!
