Pytables table into pandas DataFrame
Lots of information on how to read a csv into a pandas dataframe, but I what I have is a pyTable table and want a pandas DataFrame.
I've found how to store my pandas DataFrame to pytables... then read I want to read it back, at this point it will have:
"kind = v._v_attrs.pandas_type"
I could write it out as csv and re-read it in but that seems silly. It is what I am doing for now.
How should I be reading pytable objects into pandas?
Answer
import tables as pt
import pandas as pd
import numpy as np
# the content is junk but we don't care
grades = np.empty((10,2), dtype=(('name', 'S20'), ('grade', 'u2')))
# write to a PyTables table
handle = pt.openFile('/tmp/test_pandas.h5', 'w')
handle.createTable('/', 'grades', grades)
print handle.root.grades[:].dtype # it is a structured array
# load back as a DataFrame and check types
df = pd.DataFrame.from_records(handle.root.grades[:])
df.dtypes
Beware that your u2 (unsigned 2-byte integer) will end as an i8 (integer 8 byte), and the strings will be objects, because Pandas does not yet support the full range of dtypes that are available for Numpy arrays.