class_docstr: Example:
      >>> #The dataset is split into data, validation_data
      >>> model = ProphetForecaster(changepoint_prior_scale=0.05, seasonality_mode='additive')
      >>> model.fit(data, validation_data)
      >>> predict_result = model.predict(horizon=24)
class_docstr_tok: ["Example",":",">",">",">","#","The","dataset","is","split","into","data",",","validation_data",">",">",">","model","=","ProphetForecaster","(","changepoint_prior_scale=0.05",",","seasonality_mode='additive","'",")",">",">",">","model.fit","(","data",",","validation_data",")",">",">",">","predict_result","=","model.predict","(","horizon=24",")"]
code: def _check_data(self, data, validation_data):
      from bigdl.nano.utils.common import invalidInputError
  
      invalidInputError(
          "ds" in data.columns and "y" in data.columns,
          "data should be a pandas dataframe that has at"
          " least 2 columns 'ds' and 'y'.",
      )
      if validation_data is not None:
          invalidInputError(
              "ds" in validation_data.columns
              and "y" in validation_data.columns,
              "validation_data should be a dataframe that has at least"
              " 2 columns 'ds' and 'y'.",
          )
  
file_path: BigDL/python/chronos/src/bigdl/chronos/forecaster/prophet_forecaster.py
imports: from bigdl.chronos.forecaster.abstract import Forecaster
  from bigdl.chronos.model.prophet import ProphetModel
label_desc: Use image node_id 3 for calling the ProphetForecaster obj's underlying member method code with example usage: obj._check_data(data, validation_data) without return types