| import streamlit as st |
| import pandas as pd |
| import pickle |
| import matplotlib.pyplot as plt |
|
|
| |
| |
| |
| MODEL_PATH = "prophet_model.pkl" |
|
|
| try: |
| with open(MODEL_PATH, "rb") as f: |
| model = pickle.load(f) |
| st.success("✅ Loaded saved Prophet model.") |
| except FileNotFoundError: |
| model = None |
| st.warning("⚠ No saved model found. You can still upload CSV for chart display.") |
|
|
| |
| |
| |
| st.title("📊 Prophet Forecast Viewer") |
| uploaded_file = st.file_uploader("Upload your CSV file", type=["csv"]) |
|
|
| if uploaded_file is not None: |
| df = pd.read_csv(uploaded_file) |
|
|
| st.subheader("Data Preview") |
| st.write(df.head()) |
|
|
| |
| if model is not None: |
| try: |
| |
| df = df.rename(columns={df.columns[0]: 'ds'}) |
| df['ds'] = pd.to_datetime(df['ds']) |
|
|
| predictions = model.predict(df) |
| st.subheader("Predictions") |
| st.write(predictions[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].head()) |
|
|
| |
| fig, ax = plt.subplots(figsize=(10, 5)) |
| ax.plot(df['ds'], predictions['yhat'], label="Forecast", color="blue") |
| ax.fill_between(df['ds'], predictions['yhat_lower'], predictions['yhat_upper'], alpha=0.2) |
| ax.set_title("Forecast Chart") |
| ax.set_xlabel("Date") |
| ax.set_ylabel("Value") |
| ax.legend() |
| st.pyplot(fig) |
|
|
| except Exception as e: |
| st.error(f"Prediction failed: {e}") |
|
|
| else: |
| st.info("📂 Please upload a CSV file to begin.") |
|
|
