Python Tutorial: Learn Python For Data Science - Final thoughts: Importing data with Python

Learn more about importing data with Python: https://www.datacamp.com/courses/importing-data-in-python-part-1 We have seen a number of ways to read, print and import flat files. As a data scientist, you will most often wish to use pandas, however it was important to check out all the possible ways to import because you never know when they will be useful. In the next Chapter, we'll see just how useful pandas can be when attempting to import a variety of other file types, such as native SAS & Stata files. It is also important to remember that, due to the active development community in open source softwares, there is constant activity in file formats and ways to import data: for example, on March 29, 2016, Wes McKinney, the creator of pandas, and Hadley Wickham, of R development fame, announced a new and fast on-disk format for dataframes for R and Python, called feather . As dataframes are one the most important data structures for data scientists, let's definitely keep our eyes on feather. After learning to import many other file types in the next Chapter, you'll learn how to interact with relational databases in Python, how to tear all types of data down from the web and how to interact with APIs to fulfil your big data fix. These are all essential techniques for the modern day Data Scientist to master, and the upcoming Chapters will place you in good stead to becoming an Importing Data ninja Pythonista.