Top 5 Reasons Why Python is the Choice for Big Data

Big Data has opened the gate of opportunities for the aspirants willing to make their future in the field. There are various technologies that support Big Data, but we should always choose the best suitable and convenient one like Python. Let’s have a look at the reasons, why Python could be considered as the best suitable programming for Big Data:

1. Gives the best output: Unlike others Python is considered as the most favourite option for making the programs that work in the minimal line of code. This not only gives the pace to the development and execution process, but also identifies the data types automatically and supervene with the imprint-based nesting structure and gives the best output in less time.
2. Packages that suit the Big Data requirements, just perfect: Python has the most powerful set of packages that could satisfy the analytical needs along with most of the Data Science requirements. Following are some of the most popular Python packages:

• NumPy
• Pandas
• PyBrain
• Scipy
• Scikit-Learn
• Tensorflow

All these along with some other libraries helps a lot in processing the programming procedure likewise Cython helps in converting the code to run it in the C atmosphere. This helps in minimizing the run time and connecting the PyMySQL to MySQL databases and helps in extracting the data and executing the queries.

1. Easy to Learn: Python is easy to learn even for the beginners because of the large community, learning resources and the readable codes; these three primary reasons help in translating it to a gradual learning curve along with the direct application of concepts, which lies in the real world of the programmers. However, because of the large community the work of any programmer could be completed by any other programmer if the first one stuck somewhere.
2. This is compatible with Hadoop:The inherent compatibility of Python with the most popular open-source of the Big Data platform: Hadoophas been the yet another reason it is being preferred over other programming languages. However, the PyDoop package is the reason to access the HDFS API for Hadoop and allowing the programmers to write Hadoop MapReduce programs and applications.
3. Data Visualization: Though R has been considered as a better option than Python in this department till date, but now Python has improved its library and API; Python with Plotly and Pygal, Matplotlib, etc. is now one step ahead and can create really breathtaking data visualizations.

Sydney carter is a Python data science course by profession and has great passion for the same.