TypeError                          Traceback (most recent call last)
<ipython-input-6-b96d10f4863b> in <module>
----> 1 ddf.set_index("y")

~/workspace/dask/dask/dataframe/core.py in set_index(***failed resolving arguments***)
   4226             from .shuffle import set_index
   4227 
-> 4228             return set_index(
   4229                 self,
   4230                 other,

~/workspace/dask/dask/dataframe/shuffle.py in set_index(df, index, npartitions, shuffle, compute, drop, upsample, divisions, partition_size, **kwargs)
    160 
    161     if divisions is None:
--> 162         divisions, mins, maxes = _calculate_divisions(
    163             df, index2, repartition, npartitions, upsample, partition_size
    164         )

~/workspace/dask/dask/dataframe/shuffle.py in _calculate_divisions(df, partition_col, repartition, npartitions, upsample, partition_size)
     33     mins = partition_col.map_partitions(M.min)
     34     maxes = partition_col.map_partitions(M.max)
---> 35     divisions, sizes, mins, maxes = base.compute(divisions, sizes, mins, maxes)
     36     divisions = methods.tolist(divisions)
     37     if type(sizes) is not list:

~/workspace/dask/dask/base.py in compute(*args, **kwargs)
    566         postcomputes.append(x.__dask_postcompute__())
    567 
--> 568     results = schedule(dsk, keys, **kwargs)
    569     return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
    570 

~/workspace/dask/dask/threaded.py in get(dsk, result, cache, num_workers, pool, **kwargs)
     77             pool = MultiprocessingPoolExecutor(pool)
     78 
---> 79     results = get_async(
     80         pool.submit,
     81         pool._max_workers,

~/workspace/dask/dask/local.py in get_async(submit, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, chunksize, **kwargs)
    512                             _execute_task(task, data)  # Re-execute locally
    513                         else:
--> 514                             raise_exception(exc, tb)
    515                     res, worker_id = loads(res_info)
    516                     state["cache"][key] = res

~/workspace/dask/dask/local.py in reraise(exc, tb)
    323     if exc.__traceback__ is not tb:
    324         raise exc.with_traceback(tb)
--> 325     raise exc
    326 
    327 

~/workspace/dask/dask/local.py in execute_task(key, task_info, dumps, loads, get_id, pack_exception)
    221     try:
    222         task, data = loads(task_info)
--> 223         result = _execute_task(task, data)
    224         id = get_id()
    225         result = dumps((result, id))

~/workspace/dask/dask/core.py in _execute_task(arg, cache, dsk)
    119         # temporaries by their reference count and can execute certain
    120         # operations in-place.
--> 121         return func(*(_execute_task(a, cache) for a in args))
    122     elif not ishashable(arg):
    123         return arg

~/workspace/dask/dask/dataframe/partitionquantiles.py in percentiles_summary(df, num_old, num_new, upsample, state)
    414         data = data.codes
    415         interpolation = "nearest"
--> 416     elif np.issubdtype(data.dtype, np.integer) and not is_cupy_type(data):
    417         # CuPy doesn't currently support "nearest" interpolation,
    418         # so it's special cased in the condition above.

~/mambaforge/lib/python3.9/site-packages/numpy/core/numerictypes.py in issubdtype(arg1, arg2)
    416     """
    417     if not issubclass_(arg1, generic):
--> 418         arg1 = dtype(arg1).type
    419     if not issubclass_(arg2, generic):
    420         arg2 = dtype(arg2).type

TypeError: Cannot interpret 'string[python]' as a data type