Smoke bans and its effects!

Tobacco smoking is an activity that is widely understood to be insulting to the health. The problem then is how should we go about reducing tobacco smoking and help people quit? More specifically, are legal smoke bans the way to stop people from smoking? Sources and different studies seem to think so!

• https://www.cdc.gov/tobacco/secondhand-smoke/protection/reduce-smoking.htm#:~:text=Eleven%20studies%20found%20that%20smokefree,decrease%20in%20tobacco%20use%20prevalence.
• https://abcnews.go.com/WNT/QuitToLive/story?id=1292456
• https://tobaccocontrol.bmj.com/content/22/suppl_1/i27

import pandas as pd

df_smokeban = pd.read_csv('SmokeBan.csv')
#had a column of data on Jupyter that did no exist in original .csv file
df_smokeban = df_smokeban.drop('Unnamed: 0', axis=1)
df_smokeban.head()

	smoker	ban	age	education	afam	hispanic	gender
0	yes	yes	41	hs	no	no	female
1	yes	yes	44	some college	no	no	female
2	no	no	19	some college	no	no	female
3	yes	no	29	hs	no	no	female
4	no	yes	28	some college	no	no	female

smokeban_dict = {"smoker": "identifies whether the person is a smoker",
                "ban": "identifies whether there is a smoking ban in their area",
                "age": "person's age",
                "education": "person's highest level of education",
                "afam": "whether the person identifies as African American",
                "hispanic": "whether the person identifies as Hispanic",
                "gender": "gender that the person identifies with"}

Predictive models will be fed data of 10,000 different people, which also shows whether they are a smoker, smoking bans in their area, and claims certain other identifiable features such as age and gender. Using this data, we can then predict whether other people with such features will be smokers or no.