title: Python Dask 'Metadata parse failed' error when trying to read_parquet
body: <p>I have a data folder containing multiple .parquet files, those file were .csv file converted using pandas and pyarrow. All files have a datetime index named 'Timestamp', and five columns named 'Open', 'High', 'Low', 'Close', 'Volume', all with the same dtype=int32.</p>
  
  <p>I just want to load them all in a single Dask.Dataframe. Here's a code snippet.</p>
  
  <pre><code>import os
  import pyarrow as pa
  import pyarrow.parquet as pq
  import dask.dataframe as dd
  
  
  user = os.getlogin()
  data_path = 'C:\\Users\\%s\\data\\' % user
  
  ds = dd.read_parquet(data_path)  # error
  ds = dd.read_parquet(data_path, index='Timestamp')  # error
  </code></pre>
  
  <p>But doing so it returns me the error <strong>'fastparquet.util.ParquetException: Metadata parse failed: # data_path'</strong></p>
  
  <p>So I tried to access manually the single files' metadata.</p>
  
  <pre><code>import glob
  
  files = ['%s' % s for s in glob.glob(data_path + '*.parquet')]
  
  for file in files:
      print(pq.read_metadata(file))  # no error returned
  
  ds = dd.read_parquet(files)  # error
  ds = dd.read_parquet(files, index='Timestamp')  # error
  </code></pre>
  
  <p>What's wrong?</p>