In this video, we will review the high-level features of the Python programming language.
Python is a powerhouse language.
It is by far the most popular programming language for data science.
According to the 2019 Kaggle Data Science and Machine Learning Survey, 75% of the over
10,000 respondents from around the world reported that they use Python on a regular basis.
Glassdoor reported that in 2019 more than 75% of data science positions listed included
Python in their job descriptions.
When asked which language an aspiring data scientist should learn first, most data scientists
say Python.
You are probably thinking, why on earth is Python so popular?
Well, let’s start with the people who use Python.
If you already know how to program, then Python is great for you because it uses clear, readable
syntax.
You can do many of the things you are used to doing in other programming languages but
with Python you can do it with less code.
If you want to learn to program, it’s also a great starter language because of the huge
global community and wealth of documentation.
In fact, several different surveys in 2019 found that over 80% of data professionals
worldwide use Python.
Python is useful for many situations, including data science, AI and machine learning, web
development, and IoT devices like the Raspberry Pi.
Large organizations that use Python heavily include IBM, Wikipedia, Google, Yahoo!, CERN,
NASA, Facebook, Amazon, Instagram, Spotify, and Reddit.
Python is a powerful general-purpose programming language that can do a lot of things.
It is widely supported by a global community and shepherded by the Python Software Foundation.
1.
Python is a high-level general-purpose programming language that can be applied to many different
classes of problems.
2.
It has a large, standard library that provides tools suited to many different tasks, including
but not limited to databases, automation, web scraping, text processing, image processing,
machine learning, and data analytics.
3.
For data science, you can use Python's scientific computing libraries such as Pandas, NumPy,
SciPy, and Matplotlib.
4.
For artificial intelligence, it has TensorFlow, PyTorch, Keras, and Scikit-learn.
5.
Python can also be used for Natural Language Processing (NLP) using the Natural Language
Toolkit (NLTK).
Another great selling point is the Python community, which has a well documented history
of paving the way for diversity and inclusion efforts in the tech industry as a whole.
The Python language has a code of conduct executed by the Python Software Foundation
that seeks to ensure safety and inclusion for all, in both online and in person python
communities.
There are also communities like PyLadies that seek to create spaces for people interested
in Python to learn in safe and inclusive environments.
PyLadies is an international mentorship group with a focus on helping more women become
active participants and leaders in the Python open source community.