dask.DataFrame.read_csv: ValueError: Cannot convert NA to integer

I have the following snippet to read a csv with dask.

import dask.dataframe as dd
df = dd.read_csv('/path/to/data.csv', sep = ';', header = 0, encoding = 'utf-8')
df.head(5)

The error I get:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-12-919f0aa6a2cb> in <module>()
      1 import dask.dataframe as dd
      2 df = dd.read_csv('/path/to/data.csv', sep = ';', header = 0, encoding = 'utf-8')
----> 3 df.head(5)

/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/dataframe/core.pyc in head(self, n, compute)
    369 
    370         if compute:
--> 371             result = result.compute()
    372         return result
    373 

/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/base.pyc in compute(self, **kwargs)
     35 
     36     def compute(self, **kwargs):
---> 37         return compute(self, **kwargs)[0]
     38 
     39     @classmethod

/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/base.pyc in compute(*args, **kwargs)
    108                 for opt, val in groups.items()])
    109     keys = [var._keys() for var in variables]
--> 110     results = get(dsk, keys, **kwargs)
    111 
    112     results_iter = iter(results)

/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/threaded.pyc in get(dsk, result, cache, num_workers, **kwargs)
     55     results = get_async(pool.apply_async, len(pool._pool), dsk, result,
     56                         cache=cache, queue=queue, get_id=_thread_get_id,
---> 57                         **kwargs)
     58 
     59     return results

/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/async.pyc in get_async(apply_async, num_workers, dsk, result, cache, queue, get_id, raise_on_exception, rerun_exceptions_locally, callbacks, **kwargs)
    486                 _execute_task(task, data)  # Re-execute locally
    487             else:
--> 488                 raise(remote_exception(res, tb))
    489         state['cache'][key] = res
    490         finish_task(dsk, key, state, results, keyorder.get)

ValueError: Cannot convert NA to integer

Traceback
---------
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/async.py", line 267, in execute_task
    result = _execute_task(task, data)
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/async.py", line 249, in _execute_task
    return func(*args2)
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/dataframe/csv.py", line 43, in bytes_read_csv
    coerce_dtypes(df, dtypes)
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/dask/dataframe/csv.py", line 67, in coerce_dtypes
    df[c] = df[c].astype(dtypes[c])
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/pandas/core/generic.py", line 2632, in astype
    dtype=dtype, copy=copy, raise_on_error=raise_on_error, **kwargs)
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/pandas/core/internals.py", line 2864, in astype
    return self.apply('astype', dtype=dtype, **kwargs)
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/pandas/core/internals.py", line 2823, in apply
    applied = getattr(b, f)(**kwargs)
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/pandas/core/internals.py", line 430, in astype
    values=values, **kwargs)
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/pandas/core/internals.py", line 472, in _astype
    values = com._astype_nansafe(values.ravel(), dtype, copy=True)
  File "/home/vkcem4m/software/anaconda/lib/python2.7/site-packages/pandas/core/common.py", line 2460, in _astype_nansafe
    raise ValueError('Cannot convert NA to integer')    

[mglowacki100]

I’m facing exactly the same issue, but I use dd.read_sql_table instead of dd.read_csv. I can’t find anything similar to assume_missing=True for this. How to solve it?

[ghost]

dd.read_csv('/path/to/data.csv', sep=';', header=0, encoding='utf-8', dtype='object')

solves the problem. There is a column with mixed dtype.