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Leah Wasser
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README.md

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@@ -14,20 +14,26 @@ Welcome to the Earth Analytics Environment Repository! Here you will find a cond
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### 1. Install the Earth Lab Conda Environment on your Local Computer.
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To begin, install the conda for Python 3.x. We suggest 3.6 now.
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To begin, install git and conda for Python 3.x (we suggest 3.6).
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Installing git: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git
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Installing conda: https://www.anaconda.com/
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We recommend installing geo-related dependencies with `conda-forge`. We
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have created a custom yaml list with all of the dependencies that you will
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need to run the lessons in this course. Follow
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these steps below to get your environment ready.
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About Conda Environments: https://conda.io/docs/user-guide/tasks/manage-environments.html
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An environment for conda has been created specifically for this course. To load this run:
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An environment for conda has been created specifically for this course. To load it, run:
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`conda env create -f environment.yml`
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* Note that it takes a bit of time to run this setup
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* Also note that for the code above to work, you need to be in the directory where the `environment.yml` file lives.
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* Also note that for the code above to work, you need to be in the directory where the `environment.yml` file lives (ex: cd earth-analytics-python-env).
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To manage your conda environments, use the following commands:
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To run your earth-analytics image, use the following code:
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`docker run -it -p 8888:8888 earthlab/earth-analytics-python-env`
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`docker run --hostname localhost -it -p 8888:8888 earthlab/earth-analytics-python-env`
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NOTE: `earthlab/earth-analytics-python-env` is the name of this image as built above. To
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view all images on your computer, type

environment.yml

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- gdal
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- geocoder
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- geojson
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# natural language processing
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- tweepy
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- nltk
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# Jupyter Environment
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- notebook

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