Readme updates (#50)

* Added association updates to README and barebones

structure for additional updates on the rest of the features and deploying

* Fixed spacing in README

* Update README.md

* Update README.md

* Update README.md

README.md

@@ -3,27 +3,84 @@
 ## Overview
 A web application that displays opinions over time surrounding the police and law enforcement.
 
+## Features
+1. Map with data layers
+This feature uses government database json files to draw lines seperating zip codes and police
+precincts in two seperate data layers, and integrates features below based on user click in Map API.
+On the zip code layer it displays the zip code, neighborhood, and associated police precincts for user
+reference and on the precinct layer it allows sentiment mapping by using analysis done on survey responses
+seperated by date received and zip code association. Map API includes buttons opening seperate pages for
+detailed statistics analysis and word cloud based on strong negative and positive associations also.
+
+2. Positive and negative word associations
+
+The positive and negative associations of words within open text responses were analyzed using 
+CloudNLP. The top positive and negative associations were displayed along with a wordcloud 
+displaying all results (with size corresponding to prominence in the text and color corresponding
+to average sentiment). You can view these results for the entirety of SF or a specific precinct.
+
+3. Statistics and predictions
+
+Fetches from the Google Surveys API, transforms data for GCP Datastore, and visualizes analysis through
+the Google Charts API. This feature also runs a decision tree regression model on the survey results to get predicted
+sentiment scores for users based on their gender, age group, and whether they had a direct experience with the
+police or not. The program for regression analysis was written in Python with the Flask framework. Using crom jobs and
+a separate python service on GAE, new prediction results can be automatically generated for new survey responses.
+There is a statistics page with survey-specific details such as response time and completion,
+age and gender break down, and sentiment percentages for each precinct. 
+
 ## Tools and Technologies
 Some of the tools that will be used to build this portfolio are
 * HTML
 * CSS
 * Javascript
 * Java
+* Python
 
-## License
-This code is licensed under the Apache 2.0 License.
+## APIs
+The following APIs were used
+* Google Maps API
+* Google Charts API
+* CloudNLP (https://cloud.google.com/natural-language)
+* Wordcloud2 (https://www.npmjs.com/package/wordcloud2)
+* SciKit-Learn
+* Google Surveys API
+
+## Deploying the project
+
+To deploy the main project
+1. Install maven (https://maven.apache.org/install.html)
+2. Navigate to the capstone directory.
+3. Modify pom.xml to contain the GCP project ID.
+4. Ensure that GCP Cloud Build (https://console.developers.google.com/apis/api/cloudbuild.googleapis.com)
+and natural language (https://console.developers.google.com/apis/library/language.googleapis.com) 
+are enabled on the cloud project.
+5. Run `mvn package appengine:deploy` to deploy the project live or 
+`mvn package appengine:run` to run the project on the local server.
+
+Additional instructions for deploying the python service:
+1. Ensure that you have the requirement.txt file set up with 
+all the relevant dependencies. Do pip freeze to get the dependencies
+2. Set up a new app.yaml file with the service name, runtime, static files or
+script specified
+3. Keep these files along with your source code in a separate directory
+4. Deploy the separate service using gcloud app deploy --project [PROJECT_ID]
+5. (Optional) Include a cron.yaml file with the schedule field specified
 
 ## GitHub Checks
 This repository runs checks on every pull request and commit. You can run these
 locally from the root directory of the project.
 
 - Java Continuous Integration: Run `mvn package`
 - Java Format: Follow the instructions at
-  https://github.com/google/google-java-format to download the .jar. You can then
-  run it seperately with instructions from the the formatter README (must use java 11)
-  or run all tests together as shown below.
+  https://github.com/google/google-java-format to download the .jar. Place the jar in the
+  top level directory of the repository. You can then run it seperately with instructions 
+  from the the formatter README (must use java 11) or run all tests together as shown below.
 - JavaScript Lint:
   - One time setup: run `npm install`
   - Run `./node_modules/.bin/eslint capstone/src/.`
 - All tests can be run using `./lint` or `./lint-replace` if you want to automatically fix
   the errors found
+
+## License
+This code is licensed under the Apache 2.0 License.