Merge pull request #1945 from UV-CDAT/README_CONDA

Update README.md

README.md

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 ![platforms](http://img.shields.io/badge/platforms-linux | osx-lightgrey.svg)
 [![DOI](https://zenodo.org/badge/doi/10.5281/zenodo.50101.svg)](http://dx.doi.org/10.5281/zenodo.50101)
 
+[![Anaconda-Server Badge](https://anaconda.org/uvcdat/uvcdat/badges/installer/conda.svg)](https://conda.anaconda.org/uvcdat)
+[![Anaconda-Server Badge](https://anaconda.org/uvcdat/uvcdat/badges/downloads.svg)](https://anaconda.org/uvcdat/uvcdat)
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 Developed by partnering with ESGF and the community to create a larger problem-solving environment, UV-CDAT is an open source, easy-to-use application that links together disparate software subsystems and packages to form an integrated environment for analysis and visualization. This project seeks to advance climate science by fulfilling computational and diagnostic/visualization capabilities needed for DOE's climate research.
 
 Led by Lawrence Livermore National Laboratory (LLNL), the consortium consists of four DOE laboratories (Los Alamos, Lawrence Berkeley, LLNL, and Oak Ridge), two universities (University of Utah and the Polytechnic Institute of New York University), NASA, and two private companies (Kitware and tech-X) that will develop reusable software and workflow analysis and visualization applications for large-scale DOE climate modeling and measurements archives. The UV-CDAT concept is simple and flexible enough to interchange parts to expand for future DOE activities.