code: def randomdata(nrows=10, dtypes=None, seed=None):
      """Create a dataframe with random data
  
      Parameters
      ----------
      nrows : int
          number of rows in the dataframe
      dtypes : dict
          Mapping of column names to types.
          Valid types include {float, int, str, 'category'}
          If none is provided, this defaults to
          ``{"id": int, "x": float, "y": float}``
      seed : int (optional)
          Randomstate seed
  
      Examples
      --------
      >>> import cudf as gd
      >>> gdf = gd.datasets.randomdata()
      >>> cdf.head()  # doctest: +SKIP
              id                  x                   y
      0  1014 0.28361267466770146 -0.44274170661264334
      1  1026 -0.9937981936047235 -0.09433464773262323
      2  1038 -0.1266722796765325 0.20971126368240123
      3  1002 0.9280495300010041  0.5137701393017848
      4   976 0.9089527839187654  0.9881063385586304
      """
      if dtypes is None:
          dtypes = {"id": int, "x": float, "y": float}
      state = np.random.RandomState(seed)
      columns = {k: make[dt](nrows, state) for k, dt in dtypes.items()}
      df = pd.DataFrame(columns, columns=sorted(columns))
      return cudf.from_pandas(df)
  
file_path: cudf/python/cudf/cudf/datasets.py
imports: import numpy
  import pandas
  import cudf
  from cudf._lib.transform import bools_to_mask
  from cudf.core.column_accessor import ColumnAccessor
label_desc: Use image node_id 2 for calling a global function with example usage: randomdata(nrows, dtypes, seed) and returns: cudf