Update app.py

app.py

@@ -8,32 +8,36 @@ import altair as alt
 
 
 # Define the path to your data files relative to the script's location
-base_path = os.path.dirname(__file__)
+base_path = os.path.dirname(__file__)  # Get the directory of the current script
 data_folder = os.path.join(base_path, 'data', 'assignments_datasets', 'KIVA')
 
-# Load and concatenate datasets
+# Function to load and display data
 def load_data():
     try:
-        # Construct full paths to the data files and load each part of the dataset
-        df_part_0 = pd.read_csv(os.path.join(data_folder, 'kiva_loans_part_0.csv'))
-        df_part_1 = pd.read_csv(os.path.join(data_folder, 'kiva_loans_part_1.csv'))
-        df_part_2 = pd.read_csv(os.path.join(data_folder, 'kiva_loans_part_2.csv'))
+        # Construct full paths to the data files
+        file_paths = [
+            os.path.join(data_folder, f'kiva_loans_part_{i}.csv') for i in range(3)
+        ]
+        # Load data parts
+        data_parts = [pd.read_csv(path) for path in file_paths]
 
-        # Concatenate the subdatasets
-        df_combined = pd.concat([df_part_0, df_part_1, df_part_2], ignore_index=True)
+        # Concatenate the datasets
+        df_combined = pd.concat(data_parts, ignore_index=True)
 
         # Display the dataset header in Streamlit
         st.title("KIVA Loans Dataset Visualization")
         st.write("### Data Preview")
         st.dataframe(df_combined.head())
 
+        return df_combined
+
     except FileNotFoundError as e:
         st.error(f"File not found: {e}")
     except Exception as e:
         st.error(f"An error occurred: {e}")
 
-# Call the function to load and display data
-load_data()
+# Load and display data
+df_combined = load_data()
 
 # Introduction