code: def test_join_dfs_after_data_drop():
      log.info("Testing inner join of input df and forecast df")
      df = pd.DataFrame()
      df["ds"] = pd.date_range(start="2010-01-01", end="2010-05-01")
      df["y"] = range(0, len(df["ds"]))
  
      fcst = pd.DataFrame()
      fcst["time"] = pd.date_range(start="2009-12-01", end="2010-02-01")
      fcst["y"] = range(len(fcst["time"]))
  
      # dfs are not merged into one df
      fcst, df = df_utils.join_dfs_after_data_drop(fcst, df)
  
      # merge into one df
      df_utils.join_dfs_after_data_drop(fcst, df, merge=True)
  
imports: import logging
  import os
  import pathlib
  import matplotlib.pyplot
  import numpy
  import pandas
  import pytest
  from torch.utils.data import DataLoader
  from neuralprophet import NeuralProphet, configure, df_utils, time_dataset
  from neuralprophet.data.process import _create_dataset, _handle_missing_data
  from neuralprophet.data.transform import _normalize
label_desc: Use image node_id 19 for calling a global function with example usage: test_join_dfs_after_data_drop() without return types