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New tutorials: write section to describe sources of packages pypa#200

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+Packages are the hierarchical structuring of the module namespace using dot notation to avoid collisions between 
+module names and can be downloaded by PyPI through the pip tool which is used to install and manage software packages written in Python. 
+-	Python package installing command:
+
+	pip install some-package-name
+
+-	Python package removing command 
+
+	pip uninstall some-package-name
+
+PyPI, also known as Python Package Index is the official third-party software raspatory for Python. 
+It contains over 235,000 python packages and is free for public use, hence many package managers has PyPI as 
+their default source for packages and their dependencies. Although PyPI is popular in a global scale, it is not the only 
+software repository for python as businesses, private organizations and private projects often opt for a more private way of 
+sharing libraries and packages. Therefore, CloudRepo would often be their best choice due to their cloud based and private artifact 
+raspatory which functions the same way as PyPI to the users. 
+
+Although PyPI has immensely in popularity over the years, it is not the only index of Python packages. There are multiple competitors 
+in the market that play a similar role such as Pillow, Matplotlib, Numpy, OpenCV Python, Request, Pandas and many more. 
+
+For example, Pandas is a fast, demonstrative, and adjustable python software package that offers intuitive data-structures which users can easily 
+manipulate any type of data such as – structured or time-series data with this amazing package.
+-	Series and DataFrames to easily organize, explore, represent, and manipulate data.
+-	Perfect organization and data labelling with Smart alignment and indexing features
+-	Special features to handle missing data or value with a proper measure. 
+-	Provides clean code for easy accessibility without programming knowledge 
+-	Built-in tools that allows both reading and writing data in different web services, data-structure, and databases 
+-	Can support JSON, Excel, CSV, HDF5, and many other formats as well as merge different databases at a time with Pandas.
+