Go from messy, unstructured artifacts stored in SQL and NoSQL
databases to a neat, well-organized dataset with this quick
reference for the busy data scientist. Understand text mining,
machine learning, and network analysis; process numeric data with
the NumPy and Pandas modules; describe and analyze data using
statistical and network-theoretical methods; and see actual
examples of data analysis at work. This one-stop solution covers
the essential data science you need in Python. Data science is one
of the fastest-growing disciplines in terms of academic research,
student enrollment, and employment. Python, with its flexibility
and scalability, is quickly overtaking the R language for
data-scientific projects. Keep Python data-science concepts at your
fingertips with this modular, quick reference to the tools used to
acquire, clean, analyze, and store data. This one-stop solution
covers essential Python, databases, network analysis, natural
language processing, elements of machine learning, and
visualization. Access structured and unstructured text and numeric
data from local files, databases, and the Internet. Arrange,
rearrange, and clean the data. Work with relational and
non-relational databases, data visualization, and simple predictive
analysis (regressions, clustering, and decision trees). See how
typical data analysis problems are handled. And try your hand at
your own solutions to a variety of medium-scale projects that are
fun to work on and look good on your resume. Keep this handy quick
guide at your side whether you're a student, an entry-level data
science professional converting from R to Python, or a seasoned
Python developer who doesn't want to memorize every function and
option. What You Need: You need a decent distribution of Python 3.3
or above that includes at least NLTK, Pandas, NumPy, Matplotlib,
Networkx, SciKit-Learn, and BeautifulSoup. A great distribution
that meets the requirements is Anaconda, available for free from
www.continuum.io. If you plan to set up your own database servers,
you also need MySQL (www.mysql.com) and MongoDB (www.mongodb.com).
Both packages are free and run on Windows, Linux, and Mac OS.
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