  A large amount of data is produced every second from modern information
systems such as mobile devices, the world wide web, Internet of Things, social
media, etc. Analysis and mining of this massive data requires a lot of advanced
tools and techniques. Therefore, big data analytics and mining is currently an
active and trending area of research because of the enormous benefits
businesses and organizations derive from it. Numerous tools like Pandas, Numpy,
STATA, SPSS, have been created to help analyze and mine these huge outburst of
data and some have become so popular and widely used in the field. This paper
presents a new python-based library, DataSist, which offers high level,
intuitive and easy to use functions, and methods that helps data
scientists/analyst to quickly analyze, mine and visualize big data sets. The
objectives of this project were to (i) design a python library to aid data
analysis process by abstracting low level syntax, (ii) increase productivity of
data scientist by making them focus on what to do rather than how to do it.
This project shows that data analysis can be automated and much faster when we
abstract certain functions, and will serve as an important tool in the workflow
of data scientists.
