We use Data from covidtracking (Entire U.S. )to 12 SEP 2020 and run correlation models with a few various methods to see if any correlation exists between Positive COVId-19 test increases and Increases in Hospitalizations. Utilizing Kendal, we arrive at a .29 correlation (So no not really) Lockdowns have made virtually no statistical difference.
#covid #correlationn #nolockdowns
Code: (Part) if you need me to post more just let me know 😉 This is Python, JupyterLab _ These codes should help get you started. Remember you can also import into Excel and play with it on your own.
import matplotlib.pyplot as plt import pandas as pd from scipy.stats import spearmanr from scipy.stats import kendalltau from scipy.stats import pearsonr from scipy import stats import statsmodels.api as sm import requests import time import seaborn as sns from IPython.display import clear_output response = requests.get("https://covidtracking.com/api/v1/us/daily.csv") covid = response.content ccc = open("daily.csv","wb") ccc.write(covid) ccc.close() df = pd.read_csv("daily.csv") df= df[:-38] df = df.iloc[::-1] df1 = pd.DataFrame(df) df1 = df.reset_index(drop=True) df1.tail()