finish request api

app.py

@@ -18,6 +18,12 @@ def make_api_request(product_name, outlet_name):
         st.error(f"Error: {response.status_code}")
         return None
 
+# Function to format date
+def format_date(date_str):
+    # Convert date to datetime, add 7 hours, and format it
+    formatted_date = pd.to_datetime(date_str, unit='ms') + pd.to_timedelta("7 hours")
+    return formatted_date.strftime("%d/%m/%Y %H:%M")
+
 # Streamlit app
 st.title("Stock Movement Data")
 
@@ -36,23 +42,27 @@ if st.button("Apply"):
     if api_data:
         # Convert API response to DataFrame
         df = pd.json_normalize(api_data["data"])
+        df["stock in"] = df["stock_in_source"] + " #" + df["stock_in_id"].astype(str)
+        df["stock out"] = df["stock_out_source"] + " #" + df["stock_out_id"].astype(str)
+        df["date_in"] = df["created_at_in"].apply(format_date)
+        df["date_out"] = df["created_at"].apply(format_date)
 
         # Group by stock_price_id and aggregate details
         grouped_data = df.groupby("stock_price_id").agg(
             {"product_name": "first", "outlet_name": "first", "price": "first", 
-             "stock_in": "sum", "stock_out_total": "first", "stock_in_source": "first", 
-             "stock_in_id": "first"}
+             "stock_in": "first", "stock_out_total": "first", "stock_in_source": "first", 
+             "stock_in_id": "first", "stock in": "first", "date_in":"first"}
         ).reset_index()        
 
         # Iterate through groups and display main and detail tables
         for index, row in grouped_data.iterrows():
             # Display main table
-            st.table(pd.DataFrame([row], columns=["product_name", "outlet_name",  "stock_in_source", "stock_in_id", "price", "stock_in", "stock_out_total"]))
+            st.table(pd.DataFrame([row], columns=["stock in", "price", "stock_in", "stock_out_total", "date_in"]))
 
             # Display detail table with specific columns if the checkbox is checked
             if show_detail:
                 detail_data = df[df["stock_price_id"] == row["stock_price_id"]]
-                detail_table = detail_data[["stock_out", "stock_out_source", "stock_out_id"]]
+                detail_table = detail_data[["stock out", "stock_out", "date_out"]]
                 
                 # Use HTML to set margin-bottom to zero for the second table
                 st.markdown(f"""<style>
@@ -63,3 +73,7 @@ if st.button("Apply"):
                 
                 st.table(detail_table)
                 st.write("------")
+
+        # Display the result
+        # st.write("API Response:")
+        # st.json(api_data)