Cronocide/fitbit-web-ui-app
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Added exception for idxmax if dtype is object

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Arpan Ghosh 2023-08-04 01:11:24 -04:00
parent b13bd7bed6
commit 545320877e
1 changed files with 15 additions and 10 deletions
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src/app.py
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@ -387,6 +387,7 @@ def update_output(n_clicks, value, start_date, end_date):
# Plotting data-----------------------------------------------------------------------------------------------------------------------
fig_rhr = px.line(df_merged, x="Date", y="Resting Heart Rate", line_shape="spline", color_discrete_sequence=["#d30f1c"], title=f"<b>Daily Resting Heart Rate<br><br><sup>Overall average : {rhr_avg['overall']} bpm | Last 30d average : {rhr_avg['30d']} bpm</sup></b><br><br><br>")
if df_merged["Resting Heart Rate"].dtype != object:
fig_rhr.add_annotation(x=df_merged.iloc[df_merged["Resting Heart Rate"].idxmax()]["Date"], y=df_merged["Resting Heart Rate"].max(), text=str(df_merged["Resting Heart Rate"].max()), showarrow=False, arrowhead=0, bgcolor="#5f040a", opacity=0.80, yshift=15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_rhr.add_annotation(x=df_merged.iloc[df_merged["Resting Heart Rate"].idxmin()]["Date"], y=df_merged["Resting Heart Rate"].min(), text=str(df_merged["Resting Heart Rate"].min()), showarrow=False, arrowhead=0, bgcolor="#0b2d51", opacity=0.80, yshift=-15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_rhr.add_hline(y=df_merged["Resting Heart Rate"].mean(), line_dash="dot",annotation_text="Average : " + str(round(df_merged["Resting Heart Rate"].mean(), 1)) + " BPM", annotation_position="bottom right", annotation_bgcolor="#6b3908", annotation_opacity=0.6, annotation_borderpad=5, annotation_font=dict(family="Helvetica, monospace", size=14, color="#ffffff"))
@ -394,6 +395,7 @@ def update_output(n_clicks, value, start_date, end_date):
rhr_summary_df = calculate_table_data(df_merged, "Resting Heart Rate")
rhr_summary_table = dash_table.DataTable(rhr_summary_df.to_dict('records'), [{"name": i, "id": i} for i in rhr_summary_df.columns], style_data_conditional=[{'if': {'row_index': 'odd'},'backgroundColor': 'rgb(248, 248, 248)'}], style_header={'backgroundColor': '#5f040a','fontWeight': 'bold', 'color': 'white', 'fontSize': '14px'}, style_cell={'textAlign': 'center'})
fig_steps = px.bar(df_merged, x="Date", y="Steps Count", color_discrete_sequence=["#2fb376"], title=f"<b>Daily Steps Count<br><br><sup>Overall average : {steps_avg['overall']} steps | Last 30d average : {steps_avg['30d']} steps</sup></b><br><br><br>")
if df_merged["Steps Count"].dtype != object:
fig_steps.add_annotation(x=df_merged.iloc[df_merged["Steps Count"].idxmax()]["Date"], y=df_merged["Steps Count"].max(), text=str(df_merged["Steps Count"].max())+" steps", showarrow=False, arrowhead=0, bgcolor="#5f040a", opacity=0.80, yshift=15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_steps.add_annotation(x=df_merged.iloc[df_merged["Steps Count"].idxmin()]["Date"], y=df_merged["Steps Count"].min(), text=str(df_merged["Steps Count"].min())+" steps", showarrow=False, arrowhead=0, bgcolor="#0b2d51", opacity=0.80, yshift=-15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_steps.add_hline(y=df_merged["Steps Count"].mean(), line_dash="dot",annotation_text="Average : " + str(round(df_merged["Steps Count"].mean(), 1)) + " Steps", annotation_position="bottom right", annotation_bgcolor="#6b3908", annotation_opacity=0.8, annotation_borderpad=5, annotation_font=dict(family="Helvetica, monospace", size=14, color="#ffffff"))
@ -410,12 +412,14 @@ def update_output(n_clicks, value, start_date, end_date):
peak_summary_df = calculate_table_data(df_merged, "Peak Minutes")
peak_summary_table = dash_table.DataTable(peak_summary_df.to_dict('records'), [{"name": i, "id": i} for i in peak_summary_df.columns], style_data_conditional=[{'if': {'row_index': 'odd'},'backgroundColor': 'rgb(248, 248, 248)'}], style_header={'backgroundColor': '#00cc96','fontWeight': 'bold', 'color': 'white', 'fontSize': '14px'}, style_cell={'textAlign': 'center'})
fig_weight = px.line(df_merged, x="Date", y="weight", line_shape="spline", color_discrete_sequence=["#6b3908"], title=f"<b>Weight<br><br><sup>Overall average : {weight_avg['overall']} Unit | Last 30d average : {weight_avg['30d']} Unit</sup></b><br><br><br>")
if df_merged["weight"].dtype != object:
fig_weight.add_annotation(x=df_merged.iloc[df_merged["weight"].idxmax()]["Date"], y=df_merged["weight"].max(), text=str(df_merged["weight"].max()), showarrow=False, arrowhead=0, bgcolor="#5f040a", opacity=0.80, yshift=15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_weight.add_annotation(x=df_merged.iloc[df_merged["weight"].idxmin()]["Date"], y=df_merged["weight"].min(), text=str(df_merged["weight"].min()), showarrow=False, arrowhead=0, bgcolor="#0b2d51", opacity=0.80, yshift=-15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_weight.add_hline(y=round(df_merged["weight"].mean(),1), line_dash="dot",annotation_text="Average : " + str(round(df_merged["weight"].mean(), 1)) + " Units", annotation_position="bottom right", annotation_bgcolor="#6b3908", annotation_opacity=0.6, annotation_borderpad=5, annotation_font=dict(family="Helvetica, monospace", size=14, color="#ffffff"))
weight_summary_df = calculate_table_data(df_merged, "weight")
weight_summary_table = dash_table.DataTable(weight_summary_df.to_dict('records'), [{"name": i, "id": i} for i in weight_summary_df.columns], style_data_conditional=[{'if': {'row_index': 'odd'},'backgroundColor': 'rgb(248, 248, 248)'}], style_header={'backgroundColor': '#4c3b7d','fontWeight': 'bold', 'color': 'white', 'fontSize': '14px'}, style_cell={'textAlign': 'center'})
fig_spo2 = px.scatter(df_merged, x="Date", y="SPO2", color_discrete_sequence=["#983faa"], title=f"<b>SPO2 Percentage<br><br><sup>Overall average : {spo2_avg['overall']}% | Last 30d average : {spo2_avg['30d']}% </sup></b><br><br><br>", range_y=(90,100), labels={'SPO2':"SpO2(%)"})
if df_merged["SPO2"].dtype != object:
fig_spo2.add_annotation(x=df_merged.iloc[df_merged["SPO2"].idxmax()]["Date"], y=df_merged["SPO2"].max(), text=str(df_merged["SPO2"].max())+"%", showarrow=False, arrowhead=0, bgcolor="#5f040a", opacity=0.80, yshift=15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_spo2.add_annotation(x=df_merged.iloc[df_merged["SPO2"].idxmin()]["Date"], y=df_merged["SPO2"].min(), text=str(df_merged["SPO2"].min())+"%", showarrow=False, arrowhead=0, bgcolor="#0b2d51", opacity=0.80, yshift=-15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_spo2.add_hline(y=df_merged["SPO2"].mean(), line_dash="dot",annotation_text="Average : " + str(round(df_merged["SPO2"].mean(), 1)) + "%", annotation_position="bottom right", annotation_bgcolor="#6b3908", annotation_opacity=0.6, annotation_borderpad=5, annotation_font=dict(family="Helvetica, monospace", size=14, color="#ffffff"))
@ -424,6 +428,7 @@ def update_output(n_clicks, value, start_date, end_date):
spo2_summary_table = dash_table.DataTable(spo2_summary_df.to_dict('records'), [{"name": i, "id": i} for i in spo2_summary_df.columns], style_data_conditional=[{'if': {'row_index': 'odd'},'backgroundColor': 'rgb(248, 248, 248)'}], style_header={'backgroundColor': '#8d3a18','fontWeight': 'bold', 'color': 'white', 'fontSize': '14px'}, style_cell={'textAlign': 'center'})
fig_sleep_minutes = px.bar(df_merged, x="Date", y=["Deep Sleep Minutes", "Light Sleep Minutes", "REM Sleep Minutes", "Awake Minutes"], title=f"<b>Sleep Stages<br><br><sup>Overall average : {format_minutes(int(sleep_avg['overall']))} | Last 30d average : {format_minutes(int(sleep_avg['30d']))}</sup></b><br><br>", color_discrete_map={"Deep Sleep Minutes": '#084466', "Light Sleep Minutes": '#1e9ad6', "REM Sleep Minutes": '#4cc5da', "Awake Minutes": '#fd7676',}, height=500)
fig_sleep_minutes.update_layout(yaxis_title='Sleep Minutes', legend=dict(orientation="h",yanchor="bottom", y=1.02, xanchor="right", x=1, title_text=''), yaxis=dict(tickvals=[1,120,240,360,480,600,720], ticktext=[f"{m // 60}h" for m in [1,120,240,360,480,600,720]], title="Sleep Time (hours)"))
if df_merged["Total Sleep Minutes"].dtype != object:
fig_sleep_minutes.add_annotation(x=df_merged.iloc[df_merged["Total Sleep Minutes"].idxmax()]["Date"], y=df_merged["Total Sleep Minutes"].max(), text=str(format_minutes(df_merged["Total Sleep Minutes"].max())), showarrow=False, arrowhead=0, bgcolor="#5f040a", opacity=0.80, yshift=15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_sleep_minutes.add_annotation(x=df_merged.iloc[df_merged["Total Sleep Minutes"].idxmin()]["Date"], y=df_merged["Total Sleep Minutes"].min(), text=str(format_minutes(df_merged["Total Sleep Minutes"].min())), showarrow=False, arrowhead=0, bgcolor="#0b2d51", opacity=0.80, yshift=-15, borderpad=5, font=dict(family="Helvetica, monospace", size=12, color="#ffffff"), )
fig_sleep_minutes.add_hline(y=df_merged["Total Sleep Minutes"].mean(), line_dash="dot",annotation_text="Average : " + str(format_minutes(int(df_merged["Total Sleep Minutes"].mean()))), annotation_position="bottom right", annotation_bgcolor="#6b3908", annotation_opacity=0.6, annotation_borderpad=5, annotation_font=dict(family="Helvetica, monospace", size=14, color="#ffffff"))