python for data analysis: the python crash course comprehensive the programming from the ground up to python

In this book, Python For Data Analysis, we are going to explore a few areas
of data analysis and how they relate to and function together with Python.
These areas are separated into chapters so that you are given a thorough
explanation of how they have an individual impact when Python is used for
data analysis.

The book begins by discussing the many types of Python libraries and
describing each of their functions and capabilities. We also explain which
ones are the most popular to use and why.

After discussing the different Python libraries we then go into detail of the
Panda library and describe how the most basic library became the most
popular Python library today. After describing Pandas we then discuss how
Python data is retrieved, processed, and stored. This then leads to how data
is visualized by using graphs and charts that help to generate the
visualizations of the data. This will help you to become familiar with the
data that Python supports. A few examples include SQLite, SQL, and API.
We will then discuss the process of predictive analytics and machine
learning and how they each play a different role that relates to Python in a
certain way. Plus, it describes how machine learning can be advanced by
Python.

Finally, we will explore how Python is involved with signal processing and
time series. You will be shown many graphs again that show the data at
work .