How to read a modestly sized Parquet data-set into an in-memory Pandas DataFrame without setting up a cluster computing infrastructure such as Hadoop or Spark? This is only
Update: since the time I answered this there has been a lot of work on this look at Apache Arrow for a better read and write of parquet. Also: http://wesmckinney.com/blog/python-parquet-multithreading/
There is a python parquet reader that works relatively well: https://github.com/jcrobak/parquet-python
It will create python objects and then you will have to move them to a Pandas DataFrame so the process will be slower than pd.read_csv for example.