Upload floating.py

Added floating file update

floating.py

@@ -1,7 +1,7 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/book/LabellingTracker/13_Floating.ipynb.
 
 # %% auto 0
-__all__ = ['df', 'get_floating_grp_data', 'get_floating_summary', 'get_floating_hist', 'get_step_df', 'get_gantt']
+__all__ = ['df', 'kpi', 'get_floating_grp_data', 'get_floating_summary', 'get_floating_hist', 'get_step_df', 'get_gantt']
 
 # %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 2
 import streamlit as st
@@ -20,9 +20,23 @@ st.set_page_config(
     layout='wide'
 )
 
-# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 8
+# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 7
 # st.sidebar.success("Select a demo above.")
 
+# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 10
+def kpi(df):
+    cattle_days = df.loc[df['TAG']=='FLOATING', ['CattleFolder/Frame', 'SubFolder']].groupby('CattleFolder/Frame').count().sum().values[0]
+    cattle_floating = df.loc[df['TAG']=='FLOATING', ['CattleFolder/Frame']].nunique().values[0]
+    accounts_floating = df.loc[df['TAG']=='FLOATING', 'AccountNumber'].nunique()
+    count_user_floating = len(set(df.loc[df['TAG']=='FLOATING', 'Assigned'].dropna().str.split('/').sum()))
+    count_valid_floating = (df.loc[df['TAG']=='FLOATING', ['CattleFolder/Frame', 'SubFolder']].groupby('CattleFolder/Frame').count() > 1)['SubFolder'].sum()
+    count_exceptional_floating =(df.loc[df['TAG']=='FLOATING', ['CattleFolder/Frame', 'SubFolder']].groupby('CattleFolder/Frame').count() > 10)['SubFolder'].sum()
+    col1, col2, col3, col4 = st.columns(4)
+    col1.metric('Floating Days/Cattle', f'{cattle_days}/{cattle_floating}[{accounts_floating}]')
+    col2.metric('Labellers Floating', count_user_floating)
+    col3.metric('Valid Cattles', f'{count_valid_floating}/{cattle_floating}')
+    col4.metric('Exceptional Cattles', f'{count_exceptional_floating}/{cattle_floating}')
+
 # %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 11
 def get_floating_grp_data(df):
     grp_df = df.loc[df['TAG']=='FLOATING', ['Trial_Num', 'AccountNumber', 'AccountName', 'CattleFolder/Frame', 'TAG', 'Assigned',
@@ -61,9 +75,10 @@ def get_floating_summary(df):
     states = ['Recording','Waiting4Video', 'Waiting4Assignment', 'Labelling', 'Waiting4Labels', 'Waiting4Verification','Waiting4Completion']
     colors = dict(zip(states, ['blue', 'red', 'green', 'yellow', 'cyan', 'violet', 'pink']))
     grp_df[['AccountNumber','Assigned_sum', 'AccountName', 'CattleFolder/Frame','Recording','Waiting4Video', 'Waiting4Assignment', 'Labelling', 'Waiting4Labels', 'Waiting4Verification','Waiting4Completion']].set_index(['AccountNumber', 'AccountName', 'CattleFolder/Frame']).plot(kind='barh', stacked=True, ax=ax, color=colors);
+    fig.tight_layout()
     return fig
 
-# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 14
+# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 15
 def get_floating_hist(df, col):
     grp_df = get_floating_grp_data(df)
     fig, ax = plt.subplots()
@@ -75,7 +90,7 @@ def get_floating_hist(df, col):
     return fig
 # get_floating_hist(df, 'Recording_Duration')
 
-# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 15
+# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 17
 def get_step_df(grp_df, start_step, end_step, step_name):
     df_e = grp_df[['AccountNumber', 'AccountName','Assigned_sum', 'CattleFolder/Frame']].copy()
     df_e['Start'] = grp_df[start_step]
@@ -84,7 +99,7 @@ def get_step_df(grp_df, start_step, end_step, step_name):
     return df_e
 
 
-# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 17
+# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 19
 def get_gantt(df):
     steps = [
             {'start_step': 'Recording_Date_min', 'end_step' :'Recording_Date_max', 'step_name' : 'Recording'},
@@ -111,7 +126,8 @@ def get_gantt(df):
     # )) 
     return fig
 
-# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 21
+# %% ../../nbs/book/LabellingTracker/13_Floating.ipynb 23
+#|eval: false
 df = None
 st.write("# Floating Details")
 if 'processed_df' not in st.session_state:
@@ -122,7 +138,9 @@ else:
     colors = st.session_state['colors']
     colors2= st.session_state['colors2']
     st.markdown("## Summary Floating Durations")
+    kpi(df)
     with st.container(border=True):
+        
         st.pyplot(get_floating_summary(df))
         ncols = 3
         dcols = st.columns(ncols)