class_docstr: Class to build a Prophet Model
      
class_docstr_tok: ["Class","to","build","a","Prophet","Model"]
docstr: Refits an already trained model using a new dataset
  Useful when fitting to the full data after testing with cross validation
  :param ts_df The time series data to be used for fitting the model
  :type ts_df pd.DataFrame
  :rtype object
docstr_tok: ["Refits","an","already","trained","model","using","a","new","dataset","Useful","when","fitting","to","the","full","data","after","testing","with","cross","validation",":","param","ts_df","The","time","series","data","to","be","used","for","fitting","the","model",":","type","ts_df","pd.DataFrame",":","rtype","object"]
code: def refit(self, ts_df: pd.DataFrame) -> object:
      """
      Refits an already trained model using a new dataset
      Useful when fitting to the full data after testing with cross validation
      :param ts_df The time series data to be used for fitting the model
      :type ts_df pd.DataFrame
      :rtype object
      """
  
imports: from typing import Optional
  import logging
  import copy
  import time
  import numpy
  from sklearn.model_selection import TimeSeriesSplit
  import pandas
  from pandas.core.generic import NDFrame
  import pdb
  import dask
  import dask.dataframe
  import matplotlib.pyplot
  from prophet import Prophet
  from prophet.diagnostics import cross_validation
  from prophet.diagnostics import performance_metrics
  from prophet.plot import plot_cross_validation_metric
  from .build_base import BuildBase
  from ..utils import print_dynamic_rmse, quick_ts_plot, print_ts_model_stats
  from ..utils.logging import SuppressStdoutStderr
  from sklearn.metrics import mean_squared_error
  from prophet import Prophet
  import time
  import pdb
  import copy
  import matplotlib.pyplot
label_desc: Use image node_id 3 for calling the BuildProphet obj's underlying member method code with example usage: obj.refit(ts_df) without return types