class_docstr: The IEEE-CIS Fraud Detection Dataset https://www.kaggle.com/c/ieee-fraud-detection/overview.
class_docstr_tok: ["The","IEEE-CIS","Fraud","Detection","Dataset","https",":","\/\/www.kaggle.com\/c\/ieee-fraud-detection\/overview","."]
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."""
      train_files = {"train_identity.csv", "train_transaction.csv"}
      test_files = {"test_identity.csv", "test_transaction.csv"}
  
      train_dfs, test_dfs = {}, {}
  
      for filename in train_files.union(test_files):
          split_name = os.path.splitext(filename)[0]
          file_df = self.load_file_to_dataframe(
              os.path.join(self.raw_dataset_dir, filename)
          )
          if filename in train_files:
              train_dfs[split_name] = file_df
          elif filename in test_files:
              test_dfs[split_name] = file_df
  
      # Merge on TransactionID
      final_train = pd.merge(
          train_dfs["train_transaction"],
          train_dfs["train_identity"],
          on="TransactionID",
          how="left",
      )
      return final_train
  
imports: import os
  from typing import List
  import pandas
  from ludwig.datasets.loaders.dataset_loader import DatasetLoader
label_desc: Use image node_id 1 for calling the IEEEFraudLoader obj's underlying member method code with example usage: obj.load_unprocessed_dataframe(file_paths) and returns: final_train