Important Points about Python
Table of Content:
Current version
3.7.3
Self-defined as
Python is a programming language that lets you work quickly and integrate your systems effectively. According to the official website, the Python quote emphasizes productivity as well as its use as a glue language.
Strengths
Python has significantly more flexibility in interacting with other programming languages and is quite fast compared to R. Moreover, the pandas and scikit-learn libraries are advantageous when it comes to data manipulation and machine learning, respectively. Python is a general-purpose programming language and therefore is more universal when it comes to combining with other languages such as Java and PHP.
Hurdles
Coding in Python is more cumbersome when it comes to statistical analysis; packages in R make this process much more intuitive.
License
PSFL (BSD-like)
Popularity and usage
#4 on TIOBE index
#1 on IEEE Spectrum ranking
#2 on GitHub (by opened pull request)
#1 Packt’s 2017 Developer Skills and Salary Report Ranking
#2 Python is the second most popular language among data scientists according to O’Reilly’s 2017 US Data Science Survey, with slightly more than 60% of respondents using this language.
Backward compatibility
Promised within the 3.x releases. Python 2.7 lifetime was extended to allow migration. Python had a good track record with backward compatibility until the 3.0 release in 2008, which required nontrivial changes in almost all 2.x programs. Nine years later, all important projects either provide 2.x and 3.x compatibility or support 3.x only. No major breakage is expected when Python 4 is released.
Community
python.org. Additionally, the Python Weekly email newsletter provides significant information on the use of Python as well as related news such as jobs, new releases, and others.
Marquee users
Engineers, programmers, web developers. In general terms, Python is better for programming-oriented tasks.
Main use cases
Data wrangling, machine learning, preprocessing, text mining, web scraping. Generally speaking, Python has the upper hand over R when it comes to creating a general-purpose program that interacts more seamlessly with other programming languages. The Pandas library for data manipulation and scikit-learn for machine learning have long been favored by Python users.
Ease of learning
Better suited to users more experienced with low-level programming languages such as C++ and Java.
Salary expectations
Python-only salary: $55,000–135,000 according to the 2017 O’Reilly US Data Science Survey. In particular, those who had expertise in Python’s scikit-learn were reported to have a median salary of $100,000.
Integration
Python can integrate with Tableau through TabPy, and with Apache Spark via PySpark. This language also allows for integration with machine intelligence libraries such as TensorFlow.