5 REASONS TO CHOOSE PYTHON FOR BIG DATA PROJECTS
1
SIMPLICITY
Automatically identifies and associates data types,
and
language
is
generally
a
and
takes
less
user-friendly time
to
encode. There is also no limitation for data processing.
2
COMPATIBILITY
Hadoop is the most popular open source big data platform and Python's inherent compatibility is yet another reason to prefer it to other languages .
3
EASE OF LEARNING
It is an ideal first language for three main reasons: it has extensive learning resources, it
guarantees
readable
code,
and
it
is
surrounded by a large community. All of this translates into a gradual learning curve with the direct application of concepts in real-world programs.
4
POWERFUL PACKAGES
Python has a powerful set of packages for a wide range of data science and analysis needs . Some of the popular packages that give
this
language
an
advantage
are
NumPy, Pandas, Scipy, Scikit-learn, PyBrain, Tensorflow, Cython, PyMySQL.
5
DATA VISUALIZATION
Although R is better when it comes to data visualization, with recent packages Python for big data has improved its offering in this space. There are now APIs that can offer good results.
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