GitHub - OpenClimateProject/climate-terminal: This project aims to reflect the basic prototype of a climate terminal that consists of mainly 4 parts. The first part, Carbon stats, aims to reflects the overall metrics that could map and track the metrics associated with Carbon, be it Carbon emission, carbon price, carbon footprint, carbon #. In the prototype, we have only shown Carbon per part billion for this specific module. In the second part, we aim to target the Asset class where our aim is to provide an essence effect and description of asset class that are directly linked with climate change. For the prototype, we targeted NEw York Oil and Well Production. The third module aims to capture the Financial Market pertaining to Climate and Green Bonds and try to provide the insights related to Climate Market. In our prototype, for the sake of simplicity, we just showed forex inidicators. The tool for this specific module is intuitive. We also tried to expand the scope where user can even buy or sell stocks. Finally for the fourth tab, we focused on media sentiments, for which we developed twitter sentiment analysis tool that shows the Number of tweets, total number of words and overall sentiment score for the hot hashtags pertaining to climate change.

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This project aims to reflect the basic prototype of a climate terminal that consists of mainly 4 parts. The first part, Carbon stats, aims to reflects the overall metrics that could map and track the metrics associated with Carbon, be it Carbon emission, carbon price, carbon footprint, carbon #. In the prototype, we have only shown Carbon …

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Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
carbon		carbon
oil		oil
trader		trader
twitter_2		twitter_2
README.txt		README.txt
iframe_apps.html		iframe_apps.html

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a) In order to run the application, the user must have Python installed. If not, then use
this link to get started : https://docs.anaconda.com/anaconda/user-guide/getting-started/


Please install following Python packages before running the application:

1. Plotly 3.1.0 : Incase your plotly has higher version, downgrade your plotly to this version
2. ntlk: Natural language processing library for sentiment analysis
3. Dash: Latest version of dash should suffice
4. dash_boostrap_components
5. IPython Display
6. Flask
7. sqlite3
8. tweepy: this library will be used for scraping live tweets using Twitter API
9. sqlalchemy

In order to install these packages from anaconda prompt type in either of the following commands:
1. pip install <package name> 
2. pip install <package name> --user
3. conda install <package name>
4. conda install <package name> -c conda-forge

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After installing all the dependencies, we need to set up Flask apps for the four modules.
In order to do that:

1) Git clone the repository
2) Open Anaconda Prompts(4 anaconda prompts). The following process has to be applicable for 4 directories mentioned.
3) Open the respective directories of the modules(Carbon, Oil, Trader, twitter_2)
4) All of these directories should have app.py, which is our flask app(except twitter, it is names as twitter.py)
5) Windows Users, type in SET FLASK_APP=app.py, SET FLASK_ENV=development, flask run --port 900[0,3]
(change 0 for carbon, 1 for Asset, 2 for Stock and 3 for sentiments). For Mac Users, dont use SET command.
6) After your apps are initialized on the respective local hosts, go to your text editor and run iframe_apps.html.