docstr: Returns a pandas DataFrame in the format required for Prophet.predict() with `n` dates after the end of
  the fitted TimeSeries
docstr_tok: ["Returns","a","pandas","DataFrame","in","the","format","required","for","Prophet.predict","(",")","with","`","n","`","dates","after","the","end","of","the","fitted","TimeSeries"]
code: def _generate_predict_df(
      self, n: int, future_covariates: Optional[TimeSeries] = None
  ) -> pd.DataFrame:
      """Returns a pandas DataFrame in the format required for Prophet.predict() with `n` dates after the end of
      the fitted TimeSeries"""
  
      predict_df = pd.DataFrame(
          data={"ds": self._generate_new_dates(n)}
      )
      if self.is_logistic:
          predict_df = self._add_capacities_to_df(predict_df)
      if future_covariates is not None:
          predict_df = predict_df.merge(
              future_covariates.pd_dataframe(),
              left_on="ds",
              right_index=True,
              how="left",
          )
      return predict_df
  
imports: import logging
  import re
  from typing import Callable, List, Optional, Sequence, Union
  import numpy
  import pandas
  import prophet
  from darts.logging import execute_and_suppress_output, get_logger, raise_if, raise_log
  from darts.models.forecasting.forecasting_model import FutureCovariatesLocalForecastingModel
  from darts.timeseries import TimeSeries
label_desc: Use image node_id 5 for calling the Prophet obj's underlying member method code with example usage: obj._generate_predict_df(n, future_covariates) and returns: predict_df