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Updating README content - Issue 23 #34

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merged 2 commits into from
Mar 7, 2019
Merged

Updating README content - Issue 23 #34

merged 2 commits into from
Mar 7, 2019

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SamFritz
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@SamFritz SamFritz commented Mar 7, 2019

This pull request addresses #23 and comes on the heels of additions/modifications made by @ruebot in issue #32

This pull requests does the following:

  • tweaked some of the text placements (move suggestion of using Anaconda or Docker under requirements section)
  • added in the URLs for dependencies - when I first ran through README (with Docker listed first), I ended up having to go to each dependency's URL to install - completely fresh computer. (@ruebot @ianmilligan1) please feel free to remove if you think this is unnecessary
  • included a short definition for what Docker and Anaconda are under each sub-heading
  • included a section that gives a brief overview of what outputs and visualizations are generated through the notebook
  • adjusted links in Docker Locally section, so the URL wasn't the whole sentence

Thanks for the second and third set of eyes!!

…cies, outlines types of visuals created with notebook
@SamFritz SamFritz added the enhancement New feature or request label Mar 7, 2019
@SamFritz SamFritz self-assigned this Mar 7, 2019
@SamFritz SamFritz requested review from ruebot and ianmilligan1 March 7, 2019 03:36
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One small change, and a question.

README.md Outdated
@@ -38,6 +38,10 @@ python -m nltk.downloader punkt vader_lexicon stopwords
jupyter notebook
```

### Docker

Docker is a container-based virtual machine system that bundles dependencies together, this means you can build the docker image and it will work out of the box. To run the Jupyter Notebook via Docker, there are two options, Docker Hub and Docker Locally.
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Capitalize Docker: you can build the Docker image

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thanks for the catch!

README.md Outdated

There are several types of visualizations that you can produce in the Jupyter Notebook. A total of 14 outputs can be generated.

* *Domain Analysis* - provides information about what has been crawled (e.g. which domains) and how often.
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Should we capitalize the first word after the hyphen for each of these?

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Yes that makes sense.

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Some minor tweaks but this looks great!

README.md Outdated

There are several types of visualizations that you can produce in the Jupyter Notebook. A total of 14 outputs can be generated.

* *Domain Analysis* - provides information about what has been crawled (e.g. which domains) and how often.
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Yes that makes sense.

README.md Outdated

There are several types of visualizations that you can produce in the Jupyter Notebook. A total of 14 outputs can be generated.

* *Domain Analysis* - provides information about what has been crawled (e.g. which domains) and how often.
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Maybe change the - to a : in the list

i.e.

  • Domain Analysis: Provides information about what has been crawled (e.g. which domains) and how often.

and same for the other items in this bullet-pointed list.

README.md Outdated

This repository also uses the [Jupyter Docker Stacks](https://jupyter-docker-stacks.readthedocs.io/en/latest/index.html), which provide [a lot of helpful options to take advantage of](https://jupyter-docker-stacks.readthedocs.io/en/latest/using/common.html#docker-options).
This repository also uses the [Jupyter Docker Stacks](https://jupyter-docker-stacks.readthedocs.io/en/latest/index.html), which provide some helpful options for [customizing](https://jupyter-docker-stacks.readthedocs.io/en/latest/using/common.html#docker-options) the container environment.
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some -> several

@ianmilligan1 ianmilligan1 merged commit 5becb28 into master Mar 7, 2019
@ianmilligan1 ianmilligan1 deleted the issue-23 branch March 7, 2019 15:57
@SamFritz SamFritz mentioned this pull request Mar 7, 2019
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