refactor main app code

app.py

@@ -2,28 +2,36 @@
 import pandas as pd, panel as pn
 import hvplot.pandas # noqa
 
-# Data loading and cleaning
-df = pd.read_csv('omoku_data.csv', index_col='Date', parse_dates=True)
+# Data loading and manipulation
+df = pd.read_csv(
+    "omoku_data.csv",
+    parse_dates=['Date'],
+    index_col="Date",
+    dtype={"Remark":pd.api.types.CategoricalDtype()}
+    )
+df['Day'] = df.index.day_name().astype('category')
 
-def clean_df(df):
-    df = df[df['Remark'].isna()]
-    return df.assign(Day=df.index.day_name())
+recorded = df[df['Power_time'].notna()]
+record_days = len(recorded)
 
-cleaned_df = clean_df(df)
+days_with_power = len(recorded[recorded['Power_time'] != 0])
+power_issues = recorded[recorded['Remark'].str.contains('Repairs|Maintenance', case=False, na=False)]
 
-daily_average = cleaned_df['Power_time'].mean()
-max_power = cleaned_df['Power_time'].max()
-min_power = cleaned_df['Power_time'].min()
+percent_avai = round(days_with_power/record_days *100, 1)
+daily_average = recorded['Power_time'].mean()
 
 days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
-weekly_group = cleaned_df.groupby('Day', sort=False)[['Power_time', 'Outages']].mean().reindex(days)
+weekly_group = recorded.groupby('Day', sort=False, observed=True)[['Power_time']].mean().reindex(days)
+
+monthly_avg = recorded['Power_time'].resample("ME").mean().reset_index().set_index("Date")
+monthly_avg['Month'] = monthly_avg.index.month_name()
 
 # Plots
-box_plot = cleaned_df.hvplot.box(xlabel="Variables", ylabel="Number of hours", grid=True, title="Box Plot of Power Time and Outages")
-line_plot = cleaned_df.hvplot.line(y='Power_time', ylabel='Number of hours', title='Daily power supply')
-density_plot = cleaned_df.hvplot.kde('Power_time', xlabel='Number of hours', xlim=(0,24), yaxis=None, hover=False,
-                             title='Density distribution of power supply').opts(padding=(0,0))
-weekly_plot = weekly_group.hvplot.bar(stacked=True, rot=45, ylabel='Number of hours', title='Average power supply by week day')
+line_plot = recorded.hvplot.line(y='Power_time', ylabel='Number of hours', title='Total daily power supply')
+density_plot = recorded['Power_time'].hvplot.kde('Power_time', xlabel='Number of hours', xlim=(0,24), yaxis=None, hover=False,
+                                                 title='Density distribution of power supply')
+weekly_plot = weekly_group.hvplot.bar(rot=45, ylabel='Number of hours', title='Average power supply by week day')
+monthly_plot = monthly_avg.hvplot.bar(rot=45, hover_tooltips=['Month', 'Power_time'], hover_cols=['Month'], title="Monthly average power supply")
 
 # Dashboard
 pn.extension('tabulator', sizing_mode="stretch_width")
@@ -44,6 +52,12 @@ styles = {
 }
 
 indicators = pn.FlexBox(
+    pn.indicators.Number(
+        value=record_days,
+        name="Number of days recorded",
+        default_color="blue",
+        styles=styles,
+    ),
     pn.indicators.Number(
         value=daily_average,
         name="Average daily supply (Hrs)",
@@ -52,41 +66,41 @@ indicators = pn.FlexBox(
         styles=styles
     ),
     pn.indicators.Number(
-        value=max_power,
-        name="Highest daily supply (Hrs)",
+        value=percent_avai,
+        name="Power availability rate",
         default_color="green",
-        format=number_format,
+        format=f"{number_format}%",
         styles=styles,
     ),
     pn.indicators.Number(
-        value=min_power,
-        name="Lowest daily supply (Hrs)",
-        default_color="red",
-        format=number_format,
-        styles=styles,
+    value=len(power_issues),
+    name="Days in repairs or maintenance",
+    default_color="red",
+    styles=styles,
     ),
 )
 
 table = pn.widgets.Tabulator(df.head(10), sizing_mode="stretch_width", name="Table")
-tabs = pn.Tabs(('Daily total', line_plot), ('Weekly average', weekly_plot), ('Box plot', box_plot), ('Density distribution', density_plot), 
+tabs = pn.Tabs(('Daily total', line_plot), ('Monthly average', monthly_plot),
+               ('Weekly average',weekly_plot), ('Density distribution', density_plot),
                styles=styles, sizing_mode="scale_both", margin=10)
-logo = '<img src="https://panel.pyviz.org/_static/logo_stacked.png" width=180 height=150>'
+logo = '<img src="https://panel.holoviz.org/_static/logo_stacked.png" width=180 height=150>'
 
 text = f"""This is a [Panel](https://panel.holoviz.org) dashboard that shows the number of hours of power supply in Omoku, Rivers State, Nigeria.
 
 Omoku is divided into three (3) areas in terms of power supply and this data was collected at one of the three areas.
 
-The data was collected by calculating the total number of hours during which there was no power and subtracting it from 24 hours. 
+The data was collected by calculating the total number of hours during which there was no power and subtracting it from 24 hours.
 
 This data was collected consecutively over a period of `{len(df)}` days."""
-                        
+
 template = pn.template.FastListTemplate(
     title="Power supply dashboard",
     sidebar=[logo, text],
     sidebar_width=250,
-    main=[pn.Column('# Data Summary', indicators, '# Sample Data', table, '# Plots', tabs, sizing_mode="stretch_both")],
+    main=[pn.Column('# Data Summary', indicators, '# Sample Data', table, '# Plots', tabs)],
     main_layout=None,
     accent=ACCENT,
 )
 
-template.servable()
+template.servable()