Python is no doubt one of the best programming languages that you can learn. It is very robust and versatile and along with the right tools and libraries, you can program just about anything.

Here are some of the Python libraries and tools that are being used in different sectors.

Energy

Massive amount of energy is needed to keep the world going. And systems and applications are needed to power this producers of energy. There are various Python library available that are open-source, an example is the Pandapower.  It combines the data analysis of pandas and the power flow solver PYPOWER.

Another for wind-powered turbines is windpowerlib, which is a library to model the output of wind turbines and farms.

Basic Materials

Managing raw materials from which products are made needs to be analysed. Python Materials Genomics or pymatgen library, is robust open-source Python library for material analysis. Pymatgen is free to use and they welcome contribution in many forms.

Industrials

The Industrial sector has many divisions like Automobile, Chemical, Steel production, Brewing, Metalworking and Telecommunications. Each of them needs needs to handle large amount of data. Pandas is a flexible and powerful data analysis / manipulation library, providing labeled data structure similar to R programming language. It is used almost anywhere where large amount of data and cloud computing is involved..

Consumer Discretionary

Where consumer goods are involved, there will surely be user authentication included. OpenID allows you to use an existing account to sign in to multiple websites, without needing to create new passwords. There is a Python implementation which can be used for decentralized identity system in your application. Their GitHub page can be located here.

Healthcare

In the field of healthcare and medicine, preventing or predicting the spread of disease or ailment has been one of many focus of government services. With the availability of past data and advances in technology, determining when you are going to be sick might not just be voodoo anymore. scikit-learn is an open-source and commercially usable library. It is simple and efficient tool for data mining and data analysis.

Financial

Economy and numbers are one of the many focus of the financial sector. Tracking changes in stocks and viewing them in an easier to understand way is important for the people involved in this group. Matpotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.

Consumer Staples

The creation of produce such as food beverage,household and personal products is part of any individual living in the cities. Manufacturers and produces need to be smart and create only what is enough not only to reduce waste on profit but also avoid misuse of the raw resources available. Seaborn is a Python data visualization library that is based on matplotlib. It can help track supply and demand by providing a relatively easier to understand data instead of just numbers.

Information Technology

The IT sector is very broad and ever growing. With the availability of Platform-as-a-Service (PaaS) and different cloud providers to choose. This also exposes a lot API for developers to access. Python requests is a library used to make REST call to these API endpoints.

Communications

The exchange of information is an integral part of learning. And this not just ends after conveying or sending the data to the other party. It also includes analysis of data. NumPy is the fundamental package for scientific computing with Python. NumPy has many uses aside from its obvious scientific functionalities.

Utilities

The utilities sector refers to a category companies that provide basic amenities, such as water, sewage services, electricity, dams, and natural gas. This will need a lot of scientific computing to advance and improve the sensors used in these facilities. SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering.

Real Estate

The main segments of Real Estate are residential, commercial, and industrial. Industrial includes manufacturing buildings and property, including warehouse. With the availability of open source library and machine learning. Managing real estate can be improved by using creating different Artificial Intelligence enabled programs. A well-known and used open-source machine learning library for research and production is TensorFlow. Their code repository can be found here.