Look at Python from a data science point of view and learn proven techniques for data
visualization as used in making critical business decisions. Starting with an introduction to
data science with Python you will take a closer look at the Python environment and get
acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on
Python programming you will grasp fundamental Python programming techniques used in data
science. Moving on to data visualization you will see how it caters to modern business needs
and forms a key factor in decision-making. You will also take a look at some popular data
visualization libraries in Python. Shifting focus to data structures you will learn the
various aspects of data structures from a data science perspective. You will then work with
file I O and regular expressions in Python followed by gathering and cleaning data. Moving on
to exploring and analyzing data you will look at advanced data structures in Python. Then you
will take a deep dive into data visualization techniques going through a number of plotting
systems in Python. In conclusion you will complete a detailed case study where you'll get a
chance to revisit the concepts you've covered so far. What You Will Learn Use Python
programming techniques for data science Master data collections in Python Create engaging
visualizations for BI systems Deploy effective strategies for gathering and cleaning data
Integrate the Seaborn and Matplotlib plotting systems Who This Book Is For Developers with
basic Python programming knowledge looking to adopt key strategies for data analysis and
visualizations using Python.
