question_1.py

"""
Daria Gileva, Brandon Nguyen, Karin Stoddart
CSE 163 AA

This module contains a function that is a part of the program that explores
drug overdose deaths. It uses Washington drug overdose data. This module
allows us to answer questions about drug overdose in Washington state over a
specified time period.
"""

import plotly.express as px
import pandas as pd
from extract_and_merge import extract_xlsx


def wa_overdose_change(wa_data:  pd.ExcelFile,
                       start: float = 2016.0,
                       end: float = 2022.0) -> None:
    """
    This function takes in the Washington overdose dataset and produces
    a line graph that shows the number of drug overdose cases in Washington
    from 2016-2022. The timeframe can be changed by using default parameters.

    The plot is saved as a file named wa_overdose.png.
    """
    geography = wa_data["Geography"] == 'County'
    drug = wa_data["Drug Category"] == "Any Drug"
    year = (wa_data["Year"] >= start) & (wa_data["Year"] <= end)
    time = wa_data["Time Aggregation"] == "1 year rolling counts"
    remove_star = wa_data["Death Count"] != "*"
    county_data = wa_data[geography & drug & time & year & remove_star].copy()
    county_data["Death Count"] = county_data["Death Count"].astype("int")
    county_data = \
        county_data.groupby("Year").agg({"Death Count": "sum"}).reset_index()

    fig = px.line(
        county_data,
        x="Year",
        y="Death Count",
        title=f"Drug Overdose Deaths in WA between "
        f"{int(start)} and {int(end)}",
        markers=True
    )
    fig.update_layout(title_x=0.5, title_y=0.95, font=dict(size=15))
    fig.update_traces(line=dict(width=4), marker=dict(size=10))
    fig.write_image('wa_overdose.png')


def main():
    # Loading in the overdose data
    xlsx_file = extract_xlsx("Data/OverdoseDeathWA.xlsx",
                             "By Location and Date")

    # Call method to answer research question
    wa_overdose_change(xlsx_file)


if __name__ == "__main__":
    main()