class_docstr: The Rossmann Store Sales dataset.
class_docstr_tok: ["The","Rossmann","Store","Sales","dataset","."]
docstr: Load dataset files into a dataframe.
docstr_tok: ["Load","dataset","files","into","a","dataframe","."]
code: def load_unprocessed_dataframe(
      self, file_paths: List[str]
  ) -> pd.DataFrame:
      """Load dataset files into a dataframe."""
  
      stores_df = pd.read_csv(
          os.path.join(self.raw_dataset_dir, "store.csv")
      )
  
      train_df = pd.read_csv(
          os.path.join(self.raw_dataset_dir, "train.csv"),
          low_memory=False,
      )
      train_df = preprocess_df(train_df, stores_df)
  
      train_df["split"] = -1
      train_df.loc[train_df["Year"] == 2014, "split"] = 0
      train_df.loc[train_df["Year"] == 2015, "split"] = 2
      train_df.drop(
          train_df[train_df["split"] == -1].index, inplace=True
      )
      return train_df
  
file_path: ludwig/ludwig/datasets/loaders/rossman_store_sales.py
imports: import calendar
  import os
  from typing import List
  import numpy
  import pandas
  from ludwig.datasets.loaders.dataset_loader import DatasetLoader
label_desc: Use image node_id 1 for calling the RossmanStoreSalesLoader obj's underlying member method code with example usage: obj.load_unprocessed_dataframe(file_paths) and returns: train_df