Python's Emergence Over the Years
To start any business it is important for an entrepreneur to know about the trends where their business can expand. It’s more about future than present.
In today’s world when we talk about money making it’s more about spreading your branches in Digital Market than in any other platform. The whole world runs over tiny smart phones where
every facility is available on finger tips, that is, just a tap and you’re there.
Developing any application where your customer is a touch away is more than a brilliant idea but you must be aware of the technologies emerging in the market and there advantages in future.
In today’s article we would be discussing about one such technology which has made it’s path to being one of the top most languages used for development and other purposes.
Python is the hot topic of discussion amongst the developers and is already creating a buzz in the market because of its versatility. If we categorize, there are mainly two reasons of python being one of the most demanded technologies:
It is a web development language.
It is majorly being used in data science.
Python is being used by leading organizations like Google, NASA, CERN for all data analysis and programming purposes.
One of the fields where Python is best in the breed is Data Science. Python is being
used for weather forecast. Everyday around the world, there are thousands of weather forecasts being made. All these are then fetched and put together in a database for analyzing in depth so that the next results could be improved. Python plays a major role in it as all these analysis and reporting required lot of calculation skills. Python makes the task much easier.
Bank of America uses Python for analyzing financial data. Even facebook uses Panda (python library) for data analysis and reporting.
Two of the majorly being used libraries in Python are Panda and NumPy
Pandas are the Python Data Analysis Library; It is being used for everything from importing data from Excel spreadsheets to processing sets for time-series analysis. Basic cleanup and some advanced manipulation can be performed with Pandas’ powerful data frames.
Pandas is built on top of NumPy. NumPy is one of the earliest libraries behind Python’s data science success story. NumPy’s functions are exposed in Pandas for advanced numerical analysis.
GOOGLE has always supported the use of python. Infact, python is being used in
Google from the very beginning. The slogan is to “Use python where we can and C++ where we must”. The reason is that python is easy to maintain and helps in fast delivery. It is now the official server side language for Google.
The search engine that we use to get answers to all our queries in a matter of milliseconds is an example of how efficient Python is.