Update app.py

app.py

@@ -4,7 +4,6 @@ from time import strftime, gmtime
 import streamlit as st
 from datetime import datetime, timedelta
 import pandas as pd
-import csv
 from io import StringIO
 
 # Function to fetch data from ShareASale
@@ -38,6 +37,12 @@ def parse_csv_to_df(csv_data):
     csv_stream = StringIO(csv_data)
     return pd.read_csv(csv_stream, delimiter='|')
 
+# Create a DataFrame for merchantid to organisation name mapping
+merchant_mapping = pd.DataFrame({
+    'merchantid': [123, 456, 789],  # Replace with your actual merchant IDs
+    'organisation name': ['Company A', 'Company B', 'Company C']  # Replace with your actual organisation names
+})
+
 # Streamlit UI
 st.title("Affiliate Earnings Dashboard")
 st.sidebar.title("Settings")
@@ -51,9 +56,6 @@ api_secret_key = st.sidebar.text_input("API Secret Key", "YOUR_API_SECRET_KEY",
 start_date = st.sidebar.date_input("Start Date", datetime.now() - timedelta(days=30))
 end_date = st.sidebar.date_input("End Date", datetime.now())
 
-# Load the merchantid to organisation name mapping
-merchant_mapping = pd.read_csv('/mnt/data/a-599431.CSV')  # Modify this path as needed
-
 # Fetch data button
 if st.sidebar.button("Fetch Data"):
     # Fetch data from ShareASale
@@ -69,7 +71,7 @@ if st.sidebar.button("Fetch Data"):
     # Filter rows where action is "Transaction Created"
     df_filtered = df.loc[df['action'] == 'Transaction Created']
     
-    # Remove 'ledgerid' and 'transid' columns
+    # Remove 'ledgerid', 'transid', and 'merchantid' columns
     df_filtered = df_filtered.drop(columns=['ledgerid', 'transid', 'action', 'merchantid'])
     
     # Display the DataFrame as a table