I have been asked this tricky question many times in my career – “Python or R?”. Based on my experience, if anything, the answer to this is totally dependent on purpose for purpose and is still a question that many aspiring data scientists, business leaders and organisations are still pondering over.
It is important to have the right and best tools when providing the desired answers to the many business questions within the data science space – which isn’t as simple as it sounds. When you consider Data Analytics, Data Science, Data Strategic Planning or developing a Data Science team, where to start from in terms of languages could be a major blocker.
Python has become the de facto language of choice for organisations seeking seamless creation or upscaling skills; and its influence is evident in the cloud computing environment. The fact of the matter is, according to the 20th annual KDnuggets Software Poll, Python is still the leader – top tech companies like Alphabet’s Google and Facebook continue to use Python at the core of their frameworks.
Also, some of the essential benefits of Python are its fluency and clarity in natural readability. It is easy to learn, and it provides much flexibility in terms of scalability and productionalization. There are many libraries or packages that have been created for purpose.
Data is everywhere
Data is everywhere, big or small. And loads of companies have it but are not harnessing the capabilities of these great assets. Of course, the availability of data without the “algorithms” will not add any business values. That is why it is important for companies and business leaders to get on fast and get the tool that helps to transform their data fundamentally into the viable economic positives they desire. By choosing Python, companies will be able to utilize the potential of their data.
Deployment and Cloud Capability
The Python capability is big and its impact is felt in the areas of Machine Learning, Computer Vision, Natural Language Processing and many others. Its robustness and growing ecosystem has made it easy for many deployment and integration tools. If you use Google Cloud Platform (GCP), Amazon Web Service (AWS) or Microsoft’s Azure, you will find the convenience of use and integration with Python. As a matter of fact, cloud technologies are growing at the fastest pace with ease as Python drives most applications on cloud.
Considering a broad perspective, you might doubt if there is any question of supremacy between Python and R (or even SQL). But there is apparently a high variation in terms of needs and versatility. Python has been become a kingpin in terms of its user-friendliness, scalability and the extensive ecosystem of libraries and interoperability. Some popular libraries within Python supports the development and evolution of Artificial Intelligence (AI). Many organisations are beginning to see the reality of upskilling and taking advantage of Python in their AI driven decisions.
There is a big drive within the layers of Mango that supports the use of Python as an essential tool benefiting our consultants and clients in many ways. Many projects have had Python at their core when it comes to project execution. Also, our consultants have delivered several training courses to different organisations within both the public and private sectors across the globe, to help them harness the potential Python in their data-driven-decisions, asserting business values and helping to shape their data journey
Author: Dayo Oguntoyinbo, Data Scientist