class_docstr: The MovieLens 100K data set.  This older data set is in a different format from
  the more current data sets loaded by :class:`MovieLens`.
class_docstr_tok: ["The","MovieLens","100K","data","set",".","This","older","data","set","is","in","a","different","format","from","the","more","current","data","sets","loaded","by",":","class",":","`","MovieLens","`","."]
docstr: Return the rating data (from ``u.data``).
  
  >>> ml = ML100K()
  >>> ml.ratings
         user  item  rating  timestamp
  0       196   242     3.0  881250949
  1       186   302     3.0  891717742
  2        22   377     1.0  878887116
  3       244    51     2.0  880606923
  4       166   346     1.0  886397596
  ...
  [100000 rows x 4 columns]
docstr_tok: ["Return","the","rating","data","(","from","``","u.data","``",")",".",">",">",">","ml","=","ML100K","(",")",">",">",">","ml.ratings","user","item","rating","timestamp","0","196","242","3.0","881250949","1","186","302","3.0","891717742","2","22","377","1.0","878887116","3","244","51","2.0","880606923","4","166","346","1.0","886397596","...","[","100000","rows","x","4","columns","]"]
code: def ratings(self):
      """
      Return the rating data (from ``u.data``).
  
      >>> ml = ML100K()
      >>> ml.ratings
             user  item  rating  timestamp
      0       196   242     3.0  881250949
      1       186   302     3.0  891717742
      2        22   377     1.0  878887116
      3       244    51     2.0  880606923
      4       166   346     1.0  886397596
      ...
      [100000 rows x 4 columns]
      """
      fn = self.path / "u.data"
      ratings = pd.read_csv(
          fn,
          sep="\t",
          header=None,
          names=["user", "item", "rating", "timestamp"],
          dtype={
              "user": np.int32,
              "item": np.int32,
              "rating": np.float32,
              "timestamp": np.int32,
          },
      )
      _log.debug("loaded %s", fn)
      return ratings
  
imports: import os.path
  from pathlib import Path
  import logging
  import pandas
  import numpy
  from lenskit.util import cached
label_desc: Use image node_id 3 for calling the ML100K obj's underlying member method code with example usage: obj.ratings() and returns: ratings