In my previous blog, I have already given an overview of the various uses of Python. Among the popular uses of Python, Big Data Analytics is a buzzing topic of discussion. So, how can Python be used in Big Data Analytics?

As a follow-up, this blog will cover how Python can be used in Data Science and Big Data Analytics. 

Why Choose Python for Your Big Data Projects? 

Compatibility with Hadoop 

Apache Hadoop is a popular framework for executing Big Data projects. An advantage of choosing Python for Big Data analysis and visualization is its compatibility with Hadoop. Pydoop is a Python package offering access to Hadoop Distributed File System (HDFS). It acts as an interface to Hadoop and allows writing MapReduce programs in simple Python. The MapReduce API further helps to solve complex Big Data problems with minimal effort. 

Dedicated Packages and Libraries 

Python has a set of dedicated, open-source packages and libraries helping in Big Data Analytics. Some of the popular ones are NumPy, SciPy, mlpy, Scikit-learn, Matplotlib, PyBrain, Pandas, Theano, SymPy, and NetworkX. These libraries act as the shortcuts to implement various Big Data operations that happen on a day-to-day basis. 

Simplicity 

Python implements the slogan of Doing More with Less. Comparatively, it requires fewer code lines to execute a program. The simplicity of Python syntax is in absolute favor of Big Data projects. It has the capability to automatically identify and associate data types. For developers and data scientists, they do not have to spend extra time in structuring and memorizing the syntax. This effort can be invested in other high-priority areas. 

Easy Learning Curve 

Python has a shallow learning curve, meaning that it is fairly easy to learn for beginners. The simple syntax and code readability features make Python an easy and user-friendly programming language. This has prompted technophiles to work with Python for their data projects. 

Related reading: How Python offers the Best Business Advantages in 2019

Large Community Support 

As we already know, Big Data projects are complex in nature. By using a programming language with active community support, data scientists can easily seek solutions for their data problems. In this regard, Python proves to be a life-savior with its large and active community of developers and experts. 

Final Thoughts 

In a nutshell, Python is a tough competitor in the Big Data world. It has the know-how to provide you with strong computational capabilities. At SayOne, our Python capabilities, spanning close to a decade, are utilized to execute Big Data projects as well. In this regard, our team ensures that your complex data is broken down into meaningful insights for decision making. 

If you want to have a quick chat with our Python team, feel free to stop by. If it’s a detailed one, then drop us a message here. We will get back to you within the next 8 business hours! 

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