Update app.py

app.py

@@ -58,26 +58,51 @@ def load_overall_stats():
 
     return dk_raw, fd_raw
 
-dk_raw, fd_raw = load_overall_stats()
-
-tab1, tab2 = st.tabs(["Range of Outcomes Model", "Optimizer (Coming soon)"])
-
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-with tab1:
+dk_raw, fd_raw = load_overall_stats()
+
+tab1, tab2 = st.tabs(['Uploads and Info', 'Range of Outcomes'])
 
+with tab1:
+    st.info("The Projections file can have any columns in any order, but must contain columns explicitly named: 'Player', 'Salary', 'Position', 'Team', 'Opp', 'Minutes', 'Median', 'Own'.")
     col1, col2 = st.columns([1, 5])
 
+    with col1:
+        proj_file = st.file_uploader("Upload Projections File", key = 'proj_uploader')
+    
+        if proj_file is not None:
+                  try:
+                            proj_dataframe = pd.read_csv(proj_file)
+                  except:
+                            proj_dataframe = pd.read_excel(proj_file)
+    with col2:
+        if proj_file is not None:  
+                  st.dataframe(proj_dataframe.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+
+with tab2:
+
+    col1, col2 = st.columns([1, 9])
+
     with col1:
         if st.button("Load/Reset Data", key='reset1'):
               st.cache_data.clear()
               dk_raw, fd_raw = load_overall_stats()
+              for key in st.session_state.keys():
+                  del st.session_state[key]
+        slate_var1 = st.radio("Which data are you loading?", ('Paydirt', 'User'), key='slate_var1')
         site_var1 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var1')
         if site_var1 == 'Draftkings':
-            raw_baselines = dk_raw
+              if slate_var1 == 'User':
+                  raw_baselines = proj_dataframe
+              elif slate_var1 != 'User':
+                  raw_baselines = dk_raw
         elif site_var1 == 'Fanduel':
-            raw_baselines = fd_raw
+              if slate_var1 == 'User':
+                  raw_baselines = proj_dataframe
+              elif slate_var1 != 'User':
+                  raw_baselines = fd_raw
         split_var1 = st.radio("Are you running the full slate or crtain games?", ('Full Slate Run', 'Specific Games'), key='split_var1')
         if split_var1 == 'Specific Games':
             team_var1 = st.multiselect('Which teams would you like to include in the ROO?', options = raw_baselines['Team'].unique(), key='team_var1')
@@ -101,10 +126,10 @@ with tab1:
                         team_dict = dict(zip(working_roo.Player, working_roo.Team))
                         total_sims = 1000
 
-                        flex_file = working_roo[['Player', 'Position', 'Salary', 'Median']]
+                        flex_file = working_roo[['Player', 'Position', 'Salary', 'Median', 'Minutes']]
                         flex_file.rename(columns={"Agg": "Median"}, inplace = True)
-                        flex_file['Floor'] = flex_file['Median']*.25
-                        flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Floor'])
+                        flex_file['Floor'] = (flex_file['Median'] * .15) + (flex_file['Minutes'] * .15)
+                        flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * 1.85) + (flex_file['Minutes'] * .15)
                         flex_file['STD'] = (flex_file['Median']/4)
                         flex_file = flex_file[['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD']]
                         hold_file = flex_file