Metadata-Version: 2.1
Name: usscore
Version: 0.0.1
Summary: A package for scoring state policies of covid-19 in the US
Home-page: https://github.com/ytakefuji/scoreUS
Author: yoshiyasu takefuji
Author-email: takefuji@keio.jp
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/ytakefuji/scoreUS
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown

# scoreUS
This is a practice or exercise for students.

1. Build a program for scoring U.S. states' policies toward the COVID-19 pandemic. 
Scoring is based on the number of deaths per population (millions).

2. Then, use machine learning for understanding the relationship between its scores and other indicators.
Specify feature-importances in descending order.

Indicators such as the number of deaths, immunization rates, population, 
poverty rates, and others must be used in machine learning.

3. Examine whether the result will play a key role for policymakers in their decision-making against the pandemic.

# deaths of US states:

https://github.com/nytimes/covid-19-data/raw/master/live/us-states.csv

# vaccination rate of US states:

https://covid.ourworldindata.org/data/vaccinations/us_state_vaccinations.csv

# Use PopulationReport.csv on population by state in the US:

https://data.ers.usda.gov/reports.aspx?ID=17827

# Use pov.csv file on poverty rate by state in the US:

https://data.ers.usda.gov/reports.aspx?ID=17826

# Use health.csv:

https://www.americashealthrankings.org/explore/health-of-women-and-children/measure/outcomes_hwc_2020/state/ALL

# education

https://www.nationsreportcard.gov/profiles/stateprofile?chort=1&sub=SCI&sj=AL&sfj=NP&st=MN&year=2015R3



