code: def _get_vals(*cols, feature_type="numpy", names=None):
      """Prep input data for prediction method"""
      if feature_type == "numpy":
          vals = np.transpose([a.values for a in cols])
      elif feature_type == "pandas":
          if names is None:
              raise Exception(
                  "Must pass names argument for pandas feature type"
              )
          vals = pd.DataFrame(
              np.transpose([a.values for a in cols]), columns=names
          )
      elif feature_type == "text":
          vals = cols[0].values
      else:
          raise ValueError(
              "Unknown feature_type: {0}".format(feature_type)
          )
      return vals
  
file_path: sk-dist/skdist/distribute/predict.py
imports: import pandas
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: _get_vals() and returns: vals