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 user data (from ``u.user``).
  
  >>> ml = ML100K()
  >>> ml.users
        age gender     occupation     zip
  user
  1      24      M     technician   85711
  2      53      F          other   94043
  3      23      M         writer   32067
  4      24      M     technician   43537
  5      33      F          other   15213
  ...
  [943 rows x 4 columns]
docstr_tok: ["Return","the","user","data","(","from","``","u.user","``",")",".",">",">",">","ml","=","ML100K","(",")",">",">",">","ml.users","age","gender","occupation","zip","user","1","24","M","technician","85711","2","53","F","other","94043","3","23","M","writer","32067","4","24","M","technician","43537","5","33","F","other","15213","...","[","943","rows","x","4","columns","]"]
code: def users(self):
      """
      Return the user data (from ``u.user``).
  
      >>> ml = ML100K()
      >>> ml.users
            age gender     occupation     zip
      user
      1      24      M     technician   85711
      2      53      F          other   94043
      3      23      M         writer   32067
      4      24      M     technician   43537
      5      33      F          other   15213
      ...
      [943 rows x 4 columns]
      """
      fn = self.path / "u.user"
      users = pd.read_csv(
          fn,
          sep="|",
          header=None,
          names=["user", "age", "gender", "occupation", "zip"],
          dtype={
              "user": np.int32,
              "age": np.int8,
              "occupation": "category",
          },
      )
      _log.debug("loaded %s", fn)
      return users.set_index("user")
  
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 4 for calling the ML100K obj's underlying member method code with example usage: obj.users() and returns: users