Update app.py

app.py

@@ -3,25 +3,25 @@ import pandas as pd
 import matplotlib.pyplot as plt
 
 # Load data
-data = pd.read_csv("Graph_hugging_Y.csv")
-data2 = pd.read_csv("Graph_hugging_predict.csv")
+data_y = pd.read_csv("merged_y.csv")
+data_p = pd.read_csv("merged_p.csv")
 
 
 # Sidebar - เลือกปีเริ่มต้นและสิ้นสุด
 start_year = st.sidebar.selectbox("เลือกปีเริ่มต้น", options=list(range(2002, 2022)))
 end_year= st.sidebar.selectbox("เลือกปีสิ้นสุด", options=list(range(start_year+1, 2024)))
 
-data['date_Y'] = pd.to_datetime(data['date_Y'])
-data2['date'] = pd.to_datetime(data2['date'])
+data_y['date'] = pd.to_datetime(data_y['date'])
+data_p['date'] = pd.to_datetime(data_p['date'])
 # Filter data based on the year range
-filtered_data = data[(data["date_Y"].dt.year >= start_year) & (data["date_Y"].dt.year <= end_year)]
-filtered_data2 = data2[(data2["date"].dt.year >= start_year) & (data2["date"].dt.year <= end_year)]
+filtered_data = data_y[(data_y["date"].dt.year >= start_year) & (data_y["date"].dt.year <= end_year)]
+filtered_data2 = data_p[(data_p["date"].dt.year >= start_year) & (data_p["date"].dt.year <= end_year)]
 # Filter data based on selected years
 
 
 # สร้างตัวเลือก Selectbox
 selected_data = st.sidebar.selectbox("เลือกข้อมูลที่ต้องการโชว์",
-                                     options=["ELECTRICITY", "LPG", "DIESEL"])
+                                     options=["Electricity", "LPG", "Diesel"])
 
 # Filter data based on selected data type
 
@@ -32,14 +32,14 @@ filtered_data2 = filtered_data2[filtered_data2["symbol"] == selected_data]
 st.write("### กราฟเส้น Time Series")
 plt.figure(figsize=(10, 6))
 for fuel_type, group_data in filtered_data.groupby("symbol"):
-    if fuel_type == "ELECTRICITY":
-        plt.plot(group_data["date_Y"], group_data["Y"], label="Actual", color="yellow")
+    if fuel_type == "Electricity":
+        plt.plot(group_data["date"], group_data["Y"], label="Actual", color="yellow")
     elif fuel_type == "LPG":
-        plt.plot(group_data["date_Y"], group_data["Y"], label="Actual", color="green")
-    elif fuel_type == "DIESEL":
-        plt.plot(group_data["date_Y"], group_data["Y"], label="Actual", color="red")
+        plt.plot(group_data["date"], group_data["Y"], label="Actual", color="green")
+    elif fuel_type == "Diesel":
+        plt.plot(group_data["date"], group_data["Y"], label="Actual", color="red")
 for fuel_type,group_data in filtered_data2.groupby("symbol"):
-    plt.plot(group_data["date"], group_data["predict"], label="Predict",color="blue")
+    plt.plot(group_data["date"], group_data["Y"], label="Predict",color="blue")
 plt.xlabel("Date")
 plt.ylabel("Value")
 plt.title("Time Series")