fifa19_streamlit

app.py

@@ -16,20 +16,18 @@ st.set_page_config(
 @st.cache_resource
 def load_data():
     try:
-        with open('newdf3.pkl', 'rb') as f:
-            df3 = pickle.load(f)
-        with open('predictorsscale.pkl', 'rb') as f:
-            predictors_scaled = pickle.load(f)
-        with open('newpredictors.pkl', 'rb') as f:
-            predictors_df = pickle.load(f)
-        with open('train_predictors_val.pkl', 'rb') as f:
-            train_predictors_val = pickle.load(f)
-        with open('newfifa.pkl', 'rb') as f:
-            fifa = pickle.load(f)
-        with open('df3scaled.pkl', 'rb') as f:
-            df3scaled = pickle.load(f)
+        # Load DataFrames from CSV
+        df3 = pd.read_csv('newdf3.csv', index_col=0)
+        predictors_scaled = pd.read_csv('predictorsscale.csv', index_col=0)
+        predictors_df = pd.read_csv('newpredictors.csv', index_col=0)
+        train_predictors_val = pd.read_csv('train_predictors_val.csv', index_col=0)
+        fifa = pd.read_csv('newfifa.csv', index_col=0)
+        df3scaled = pd.read_csv('df3scaled.csv', index_col=0)
+        
+        # Only the model needs to stay as pickle
         with open('finalxbrmodel.pkl', 'rb') as f:
             xbr = pickle.load(f)
+            
         return df3, predictors_scaled, predictors_df, train_predictors_val, fifa, df3scaled, xbr
     except Exception as e:
         st.error(f"Error loading data: {str(e)}")

convert_pickles.py

@@ -0,0 +1,15 @@
+import pandas as pd
+import pickle
+
+# Convert DataFrame pickles to CSV
+pickle_files = ['newdf3.pkl', 'predictorsscale.pkl', 'newpredictors.pkl', 
+                'train_predictors_val.pkl', 'newfifa.pkl', 'df3scaled.pkl']
+
+for file in pickle_files:
+    try:
+        df = pd.read_pickle(file)
+        csv_file = file.replace('.pkl', '.csv')
+        df.to_csv(csv_file, index=True)
+        print(f"Converted {file} to {csv_file}")
+    except Exception as e:
+        print(f"Error converting {file}: {str(e)}") 

requirements.txt

@@ -1,5 +1,5 @@
 streamlit
 numpy
-pandas
+pandas==1.5.3
 scikit-learn
 pickle5