The Beauty in Data

Beauty in data is not merely in its collection and storage, 

 rather in its processes; 

Preparatory nurturing - error handling, cleaning, missing values, duplications, merging,
aggregation, summarization.

   EDA - analysis and visualization, 

telling stories, 

 giving insights and 

 supporting decision making.

The Data Science Research Center

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Anaconda Python Distribution Python 3.3 linking

Anaconda Python Distribution

Anaconda is a pre-packaged Python distribution for scientific users. [1]
Direct your browser to http://continuum.io/downloads.html ; download the version for your machine. Then follow the steps described for your machine here: http://docs.continuum.io/anaconda/install.html. You do not need to worry about setting the paths yet. By default, the Anaconda Python distribution uses Python 2.7 – we want Python 3.3. For this reason, we need to create a corresponding environment. In a shell (see below for opening one), go to the directory where you installed Anaconda.

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On Windows, type:
cd Scripts conda create -n py33 python=3.3 anaconda

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On MacOS / Linux, type:
cd bin ./conda create -n py33 python=3.3 anaconda Accept the list of things to be installed and wait for a bit. This will install an Anaconda Python environment based on Python 3.3 to the envs/py33 subdirectory of your Anaconda installation.

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Data Sciencing

The art of data sciencing(i.e living in and with science) has existed right from time immemorial.... Our continuous and sustainable levity, is and has been dependent on evolution of knowledge, Past on from generation to generation, from species to species as data....in our DNA, books or environment.


"" Sherlock Holmes(movie) ---- Data Data Data How can you build a house without bricks ""

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