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| import streamlit as st | |
| import pandas as pd | |
| from prophet import Prophet | |
| class ProphetModel: | |
| def predict(df: pd.DataFrame, **kwargs) -> pd.DataFrame: | |
| st1, st2 = st.columns(2) | |
| params = { | |
| "growth": kwargs.get("growth", "linear"), | |
| "interval_width": kwargs.get("interval_width", 0.95), | |
| } | |
| # st.write(params) | |
| st.write(kwargs) | |
| if "cap" in kwargs: | |
| df["cap"] = float(kwargs.get("cap")) | |
| period = kwargs.get("period", 7) | |
| # -- train model | |
| m = Prophet(**params) | |
| m.fit(df) | |
| future = m.make_future_dataframe(periods=period) | |
| if "cap" in kwargs: | |
| future["cap"] = float(kwargs.get("cap")) | |
| forecast = m.predict(future) | |
| # -- display output | |
| cols = ["ds", "yhat", "yhat_lower", "yhat_upper"] | |
| temp_ = forecast.copy() | |
| temp_["ds"] = temp_["ds"].apply(lambda x: x.strftime("%Y-%m-%d")) | |
| st.write(f"future={period}days") | |
| st.write(temp_[cols]) | |
| fig1 = m.plot(forecast) | |
| fig2 = m.plot_components(forecast) | |
| from prophet.plot import plot_plotly, plot_components_plotly | |
| st1.markdown("> forecasts") | |
| st1.plotly_chart(plot_plotly(m, forecast, trend=True), use_container_width=True) | |
| st2.markdown("> forecast components") | |
| st2.plotly_chart(plot_components_plotly(m, forecast), use_container_width=True) | |
| # -- download results | |
| from forecast.utils import get_table_download_link | |
| st.markdown(get_table_download_link(forecast), unsafe_allow_html=True) | |
| st.success("Forecast completed ✨") | |
| return df | |