From 1d712e911b8383976110bb49d6629eeee4a44269 Mon Sep 17 00:00:00 2001 From: luutuankiet <56199834+luutuankiet@users.noreply.github.com> Date: Sun, 25 Feb 2024 16:48:00 -0500 Subject: [PATCH] new average calc and remove -abs to fix issue all time delta are in future --- app/charts/main.py | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/app/charts/main.py b/app/charts/main.py index 5abfd8d..eaca8b4 100644 --- a/app/charts/main.py +++ b/app/charts/main.py @@ -332,7 +332,7 @@ def highlight_row(row): created_df_delta = created_df - created_df_delta['max_day_created_timestamp'] = -abs(pd.Timestamp.now(tz=adj_timezone) - created_df_delta['max_day_created_timestamp'].dt.tz_localize(tz=adj_timezone)) + created_df_delta['max_day_created_timestamp'] = abs(pd.Timestamp.now(tz=adj_timezone) - created_df_delta['max_day_created_timestamp'].dt.tz_localize(tz=adj_timezone)) created_df_delta['max_day_created_timestamp'] = created_df_delta['max_day_created_timestamp'].apply(lambda x: humanize.naturaltime(x)) create_progress = pd.merge(created_df_delta,filtered_lvl1_lvl2_progress,on=['fld_folder_name','l_list_name'],how='left') create_progress = create_progress.style.map( @@ -343,7 +343,7 @@ def highlight_row(row): active_df_delta = active_df - active_df_delta['max_day_active_timestamp'] = -abs(pd.Timestamp.now(tz=adj_timezone) - active_df_delta['max_day_active_timestamp'].dt.tz_localize(tz=adj_timezone)) + active_df_delta['max_day_active_timestamp'] = abs(pd.Timestamp.now(tz=adj_timezone) - active_df_delta['max_day_active_timestamp'].dt.tz_localize(tz=adj_timezone)) active_df_delta['max_day_active_timestamp'] = active_df_delta['max_day_active_timestamp'].apply(lambda x: humanize.naturaltime(x)) active_progress = pd.merge(active_df_delta,filtered_lvl1_lvl2_progress,on=['fld_folder_name','l_list_name'],how='left') active_progress = active_progress.style.map( @@ -356,7 +356,7 @@ def highlight_row(row): completed_df_delta = completed_df - completed_df_delta['max_day_completed_timestamp'] = -abs(pd.Timestamp.now(tz=adj_timezone) - completed_df_delta['max_day_completed_timestamp'].dt.tz_localize(tz=adj_timezone)) + completed_df_delta['max_day_completed_timestamp'] = abs(pd.Timestamp.now(tz=adj_timezone) - completed_df_delta['max_day_completed_timestamp'].dt.tz_localize(tz=adj_timezone)) completed_df_delta['max_day_completed_timestamp'] = completed_df_delta['max_day_completed_timestamp'].apply(lambda x: humanize.naturaltime(x)) complete_progress = pd.merge(completed_df_delta,filtered_lvl1_lvl2_progress,on=['fld_folder_name','l_list_name'],how='left') complete_progress = complete_progress.style.map( @@ -370,20 +370,19 @@ def highlight_row(row): col1,col2,col3 = st.columns(3) - col1.metric("avg completed",value=completed_df.groupby('day_of_year')['tasks_completed'].sum().mean() if completed_df_delta.shape[0] > 0 else None, + col1.metric("avg completed",value=completed_df.groupby('day_of_year')['tasks_completed'].sum() / completed_df.groupby('day_of_year')['day_of_year'].count() if completed_df_delta.shape[0] > 0 else None, delta=f"last item {completed_df_delta.iloc[0,3] }" if completed_df_delta.shape[0] > 0 else None, delta_color="off") - col2.metric("avg created",value=created_df.groupby('day_of_year')['tasks_created'].sum().mean() if created_df_delta.shape[0] > 0 else None, + col2.metric("avg created",value=created_df.groupby('day_of_year')['tasks_created'].sum() / created_df.groupby('day_of_year')['day_of_year'].count() if created_df_delta.shape[0] > 0 else None, delta=f"last item {created_df_delta.iloc[0,3]}" if created_df_delta.shape[0] > 0 else None, delta_color="off") - col3.metric("avg active",value=active_df.groupby('day_of_year')['tasks_active'].sum().mean() if active_df_delta.shape[0] > 0 else None, + col3.metric("avg active",value=active_df.groupby('day_of_year')['tasks_active'].sum() / active_df.groupby('day_of_year')['day_of_year'].count() if active_df_delta.shape[0] > 0 else None, delta=f"last item {active_df_delta.iloc[0,3] }" if active_df_delta.shape[0] > 0 else None, delta_color="off") - with st.expander("complete",expanded = True): st.dataframe(