“Data science” is just about as broad of a term as they come. It may be easiest to describe what it is by listing its more concrete components: Data exploration & analysis. Included here: Pandas; NumPy; SciPy; a helping hand from Python's Standard Library.
Python-with-Data-Science
Data Science: Data Science is a detailed study of the flow of information from the colossal amounts of data present in an organization's repository. It involves obtaining meaningful insights from raw and unstructured data which is processed through analytical, programming, and business skills
This Repository will introduce the developers to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.
