def METHOD_NAME(file_pattern):
  """Read data from Google Cloud Storage, split into train and validation sets.
  Assume that the data on GCS is in csv format without header.
  The column names will be provided through metadata
  Args:
    file_pattern: (string) pattern of the files containing training data.
    For example: [gs://bucket/folder_name/prefix]
  Returns:
    pandas.DataFrame
  """
  # Download the files to local /tmp/ folder
  df_list = []
  for filepath in gfile.Glob(file_pattern):
    with gfile.Open(filepath, 'r') as f:
      # Assume there is no header
      df_list.append(pd.read_csv(f, names=metadata.CSV_COLUMNS))
  data_df = pd.concat(df_list)
  return data_df