What goes into creating business value from raw data? Is Python be the data science language for you? Explore more about this programming language and get a peek at courses available in the library.
(upbeat music) - Data science, analytics, data visualization, and big data. They're all important parts of the mission critical task of generating business value from raw data. The coding, analysis, and subject matter expertise that go into data science make it a pivotal stepping stone on the journey from data to value. I love using Python for data science because it simplifies this complex work to a few human-readable lines of code. - [Kumaran] Let's say you have a massive amount of text that you need to analyze. That's a fairly likely scenario, considering more and more text is being generated today. It takes the form of messages, emails, blogs, and comments on social media, and the need to understand, analyze, and act on this data is also growing. As such, text processing and analytics is a key skill for any data professional. I will show you the techniques and tools available for text analytics and predictions in Python. - [Miki] Python is a very mature and popular language. Python has become a big player in the data science scene, and you can find much more data science related work in the Python community. From libraries and frameworks to user meetings, and the number of data-related talks at conventions. I'd say that ScientificPython is one of Python's killer apps. The great thing about using Python for data science is that you can use the same language for both research and production. Data scientists can train sophisticated algorithm, and use it in production with ease. Python is also a great general purpose language, and since about 80 percent of our work as data scientists involve getting data from various sources, and cleaning it, Python is a great thing. - Writing code should be fun, productive, and perhaps most of all, efficient. You can describe Python using every one of those words, and probably many more, and one of the major reasons for that is the comprehensive library of prebuilt code that comes as part of the language. The Python Standard Library makes the process of building applications that use features like manipulating text information, working with files and directories, processing numerical data, and accessing information over the internet, much easier. The Python Standard Library has modules for a wide variety of programming needs, and chances are, if you've got a programming challenge, the Standard Library has you covered. - [Jonathan] Pandas is an open-source library that provides easy-to-use data analysis tools for the Python programming language. It will cover topics such as Series and DataFrames, plotting, indexing, GroupBy, stack and unstack, and some data visualizations.