python - Creating pandas.DataFrame from numpy.array -


What I'm doing here: 

  NP import as Panda PDS As Np .___ version__ # '1.8.1' pd.___ version_ # '0.14.1-107-G381a289'

Here are some fake data: 

  foo = Np.arange (5) times = np.random.randn (30). Renewal ((5, 3, 2))

I want to get the foo and bar in a pd. In DataFrame . To my surprise, the following does not work (even if foo.shape [0] == times [0] ): 

  df = pd DataFrame #from_dict (dict (foo = foo, bar = bar) # Exception: The data must be 1-dimension

This works: 

  df = Pd.DataFrame.from_dict (dict (foo = foo.tolist), bar = bar.tolist ()) DF ['bar'] = df ['bar']. Apply this roundabout method to change my  array  in my nested  list  and then apply it to   
 > Convert back to an array via Apply  is annoying. Is there any more simple way I just do not know?


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