Python is a popular programming language- how popular depends on who you ask. The results of the 2018 Stack Overflow Developer Survey rank Python as the #7 most popular language among professional developers. But Python takes the #3 spot for the “most loved” language by developers surveyed. The 19th annual KDnuggets Software Poll ranks Python as the #1 tool for analytics, data science, and machine learning.
Python is Popular for Many Reasons
Python is an open source, general-purpose programming language designed so that it is simple to read and to write. Python can be used for a wide range of applications and use cases such as web development, machine learning, and remote control of a Raspberry Pi robot. You can build just about any application with Python.
Compared to other languages, Python typically requires less coding and is easier to debug, deploy, and maintain. It is also easy to learn, so even a novice programmer can pick up Python quickly. Python is supported by a vast global community of developers. And Python is supported by major tech companies like Google, Instagram, Netflix, and Dropbox.
Python is a powerful programming language, but there are cases where a language like R, C++, Java, or Julia may be the better option or a combination of languages. For example, R is an excellent choice when it comes to statistical learning because it was designed as a statistical language.
Tons of Python Libraries
One of the biggest reasons Python is a popular programming language is the availability of more than 150,000 Python-supported software libraries. No matter what the industry or job position, odds are, you can find a pre-built Python library for your specific use case.
Our data scientists have discovered many great Python libraries, and have extended Python libraries for specific marketing use cases such as marketing analytics and marketing segmentation. You can find Python libraries for machine learning such as TensorFlow, NLTK (Natural Language Toolkit), and Scikit-learn. One of the most downloaded Python packages of all time is Python Requests, a simple HTTP library for Python.
Python is Used in Marketing
Data scientists and engineers are using machine learning to build platforms for a wide range of marketing use cases including automating customer analytics and predictive analytics. Python is a popular choice when it comes to data science and machine learning because of its flexibility when it comes to production builds and integration with web applications. Python (along with machine learning) can be used to create marketing applications that uncover insights from customer data. These insights could include customer purchasing patterns, propensity to buy, and price sensitivity.
A New Title in Marketing: Growth Hacker
A new job title has recently emerged in marketing, one that emphasizes the need for marketers to have programming skills- that job title is “growth hacker.” Andrew Chen, a general partner at Andreessen Horowitz, explains in a blog post that the job of a growth hacker combines the skills of a marketer and a coder. A growth hacker relies primarily on technological tools to increase business growth, tools such as APIs, multivariate testing, and super-platforms (e.g. Amazon, Apple, Facebook, and Google). Chen says that “the fastest way to spread your product is by distributing it on a platform using APIs, not MBAs. Business development is now API-centric, not people-centric.”
The role of a marketer is becoming a technical one that requires coding skills and knowing your way around an API. And Python may soon become a must-have tool for data scientists and marketers alike.
Janet Wagner is a Zylotech contributing writer.
If you liked this post, check out Why ecommerce is a goldmine for customer data tracking.
Originally published at www.zylotech.com.
