Merge pull request #16 from Haleshot/010-Mustjaab

Add `010-mustjaab`

010-Mustjaab/Analysis-of-wait-times.py

@@ -0,0 +1,313 @@
+# /// script
+# requires-python = ">=3.12"
+# dependencies = [
+#     "pandas==2.2.3",
+#     "plotly==5.24.1",
+#     "marimo",
+# ]
+# ///
+import marimo
+
+__generated_with = "0.9.7-dev1"
+app = marimo.App(width="medium")
+
+
+@app.cell
+def __():
+    import marimo as mo
+    import pandas as pd
+    import plotly.express as px
+    return mo, pd, px
+
+
+@app.cell
+def __(mo):
+    mo.md(r"""<h1> Analysis of Wait Times for Priority Procedures </h1>""").style(
+        {"background-color": "crimson"}
+    )
+    return
+
+
+@app.cell
+def __(mo):
+    mo.md(
+        r"""
+        ## Sections
+        <ul>
+            <li> General Overview</li>
+            <li> 50th Percentiles </li>
+            <li> Comparing 90th Percentiles </li>
+        </ul>
+        """
+    )
+    return
+
+
+@app.cell
+def __(pd):
+    Wait_Times = pd.read_csv("Wait_Times_Data.csv")
+    return (Wait_Times,)
+
+
+@app.cell
+def __(mo):
+    mo.md(
+        r"""
+        ## General Overview
+        <p> This notebook will compare the percentile of wait days (50th, and 90th) for various critical procedures in hospitals across Canada. Data was obtained from the <a href = "https://www.cihi.ca/en/access-data-and-reports/data-tables?sort_by=field_published_date_value&sort_order=DESC&page=1"> Canadian Institute for Health Information </a> (CIHI). Percentiles help us get a better understanding where a value in a dataset stands in comparison to others - is it on the lower end of the set? Is it on the higher end? Or is it smack in the middle? You can learn more about percentiles <a href = "https://statisticsbyjim.com/basics/percentiles/"> here. </a> </p>
+        """
+    )
+    return
+
+
+@app.cell
+def __(mo):
+    _df = mo.sql(
+        f"""
+        SELECT * 
+        FROM "Wait_Times"
+        WHERE Indicator_result !='n/a'
+        LIMIT 50
+        """
+    )
+    return
+
+
+@app.cell
+def __(mo):
+    mo.md(r"""<h2 id='Bladder'> 50th Percentiles </h2>""")
+    return
+
+
+@app.cell
+def __(Bladder_Cancer_df, CABG_df, Lung_Cancer_df, mo):
+    Operation_Options = {
+        "Bladder Cancer Surgery": Bladder_Cancer_df,
+        "CABG": CABG_df,
+        "Lung Cancer Surgery": Lung_Cancer_df,
+    }
+
+    Operation_Choice = mo.ui.dropdown(
+        options=["Bladder Cancer Surgery", "CABG", "Lung Cancer Surgery"],
+        value="Bladder Cancer Surgery",
+    )
+    return Operation_Choice, Operation_Options
+
+
+@app.cell
+def __(Operation_Choice, Operation_Options):
+    Operation_Bar = Operation_Options[Operation_Choice.value]
+    return (Operation_Bar,)
+
+
+@app.cell
+def __(mo):
+    Bladder_Cancer_df = mo.sql(
+        f"""
+        SELECT Province_territory,Indicator,Metric,Data_year,Unit_of_measurement,Indicator_result
+        FROM "Wait_Times"
+        WHERE Province_territory !='Canada'
+        AND Indicator = 'Bladder Cancer Surgery'
+        AND Metric = '50th Percentile'
+        AND Data_year IN ('2013', '2023')
+        And Unit_of_measurement = 'Days'
+        AND Indicator_result !='n/a'
+        ORDER BY Indicator_result ASC
+        """, output=False
+    )
+    return (Bladder_Cancer_df,)
+
+
+@app.cell
+def __(mo):
+    CABG_df = mo.sql(
+        f"""
+        SELECT Province_territory,Indicator,Metric,Data_year,Unit_of_measurement,Indicator_result
+        FROM "Wait_Times"
+        WHERE Province_territory !='Canada'
+        AND Indicator = 'CABG'
+        AND Metric = '50th Percentile'
+        AND Data_year IN ('2013', '2023')
+        And Unit_of_measurement = 'Days'
+        AND Indicator_result !='n/a'
+        ORDER BY Indicator_result ASC
+        """, output=False
+    )
+    return (CABG_df,)
+
+
+@app.cell
+def __(mo):
+    Lung_Cancer_df = mo.sql(
+        f"""
+        SELECT Province_territory,Indicator,Metric,Data_year,Unit_of_measurement,Indicator_result
+        FROM "Wait_Times"
+        WHERE Province_territory !='Canada'
+        AND Indicator = 'Lung Cancer Surgery'
+        AND Metric = '50th Percentile'
+        AND Data_year IN ('2013', '2023')
+        And Unit_of_measurement = 'Days'
+        AND Indicator_result !='n/a'
+        ORDER BY Indicator_result ASC
+        """, output=False
+    )
+    return (Lung_Cancer_df,)
+
+
+@app.cell
+def __(Operation_Choice):
+    Operation_Choice
+    return
+
+
+@app.cell
+def __(Operation_Bar, px):
+    Bladder_Bar = px.bar(Operation_Bar,x='Province_territory',y='Indicator_result', color='Data_year', barmode='group')
+    Bladder_Bar
+    return (Bladder_Bar,)
+
+
+@app.cell
+def __(mo):
+    mo.md(r"""<caption> Bar chart comparing 50th percentiles of wait times between 2013 and 2023 across provinces.</caption>""").style({'background-color':'brown','color':'white'})
+    return
+
+
+@app.cell
+def __(mo):
+    mo.md(r"""## Comparing 90th Percentiles""")
+    return
+
+
+@app.cell
+def __(mo):
+    Bladder_Cancer_90th_Percentile_2013_df = mo.sql(
+        f"""
+        SELECT Province_territory,Indicator,Metric,Data_year,Unit_of_measurement,Indicator_result
+        FROM "Wait_Times"
+        WHERE Province_territory !='Canada'
+        AND Indicator = 'Bladder Cancer Surgery'
+        AND Metric = '90th Percentile'
+        AND Data_year = '2013'
+        And Unit_of_measurement = 'Days'
+        AND Indicator_result !='n/a'
+        ORDER BY Indicator_result ASC
+        """, output=False
+    )
+    return (Bladder_Cancer_90th_Percentile_2013_df,)
+
+
+@app.cell
+def __(mo):
+    Bladder_Cancer_90th_Percentile_2023_df = mo.sql(
+        f"""
+        SELECT Province_territory,Indicator,Metric,Data_year,Unit_of_measurement,Indicator_result
+        FROM "Wait_Times"
+        WHERE Province_territory != 'Canada'
+        AND Indicator = 'Bladder Cancer Surgery'
+        AND Metric = '90th Percentile'
+        AND Data_year IN ('2023')
+        And Unit_of_measurement = 'Days'
+        AND Indicator_result !='n/a'
+        ORDER BY Indicator_result ASC
+        """, output=False
+    )
+    return (Bladder_Cancer_90th_Percentile_2023_df,)
+
+
+@app.cell
+def __(mo):
+    Lung_Cancer_90th_Percentile_2013_df = mo.sql(
+        f"""
+        SELECT Province_territory,Indicator,Metric,Data_year,Unit_of_measurement,Indicator_result
+        FROM "Wait_Times"
+        WHERE Province_territory != 'Canada'
+        AND Indicator = 'Lung Cancer Surgery'
+        AND Metric = '90th Percentile'
+        AND Data_year IN ('2013')
+        And Unit_of_measurement = 'Days'
+        AND Indicator_result !='n/a'
+        ORDER BY Indicator_result ASC
+        """, output=False
+    )
+    return (Lung_Cancer_90th_Percentile_2013_df,)
+
+
+@app.cell
+def __(mo):
+    Lung_Cancer_90th_Percentile_2023_df = mo.sql(
+        f"""
+        SELECT Province_territory,Indicator,Metric,Data_year,Unit_of_measurement,Indicator_result
+        FROM "Wait_Times"
+        WHERE Province_territory != 'Canada'
+        AND Indicator = 'Bladder Cancer Surgery'
+        AND Metric = '90th Percentile'
+        AND Data_year IN ('2023')
+        And Unit_of_measurement = 'Days'
+        AND Indicator_result !='n/a'
+        ORDER BY Indicator_result ASC
+        """, output=False
+    )
+    return (Lung_Cancer_90th_Percentile_2023_df,)
+
+
+@app.cell
+def __(
+    Bladder_Cancer_90th_Percentile_2013_df,
+    Bladder_Cancer_90th_Percentile_2023_df,
+    Lung_Cancer_90th_Percentile_2013_df,
+    Lung_Cancer_90th_Percentile_2023_df,
+    px,
+):
+    Bladder_Cancer_2013 = px.pie(Bladder_Cancer_90th_Percentile_2013_df,values='Indicator_result', names='Province_territory')
+
+    Bladder_Cancer_2023 = px.pie(Bladder_Cancer_90th_Percentile_2023_df,values='Indicator_result', names='Province_territory')
+
+    Lung_Cancer_2013 = px.pie(Lung_Cancer_90th_Percentile_2013_df,values='Indicator_result', names='Province_territory')
+
+    Lung_Cancer_2023 = px.pie(Lung_Cancer_90th_Percentile_2023_df,values='Indicator_result', names='Province_territory')
+    return (
+        Bladder_Cancer_2013,
+        Bladder_Cancer_2023,
+        Lung_Cancer_2013,
+        Lung_Cancer_2023,
+    )
+
+
+@app.cell
+def __(mo):
+    Ten_Year_Journey = mo.ui.slider(2013,2023,10,value=2023, label = 'Ten Year Slider:')
+    Ten_Year_Journey
+    return (Ten_Year_Journey,)
+
+
+@app.cell
+def __(Ten_Year_Journey):
+    Time_Parameter = Ten_Year_Journey.value
+    return (Time_Parameter,)
+
+
+@app.cell
+def __(Bladder_Cancer_2013, Bladder_Cancer_2023):
+    def Percentile_Time_Machine(Time_Parameter):
+        if Time_Parameter == 2013:
+            return Bladder_Cancer_2013
+        if Time_Parameter == 2023:
+            return Bladder_Cancer_2023
+    return (Percentile_Time_Machine,)
+
+
+@app.cell
+def __(Percentile_Time_Machine, Time_Parameter):
+    Percentile_Time_Machine(Time_Parameter)
+    return
+
+
+@app.cell
+def __(mo):
+    mo.md(r"""<caption> Pie charts of 90th percentile values for each province over a span of 10 years.</caption>""").style({'background-color':'indigo'})
+    return
+
+
+if __name__ == "__main__":
+    app.run()