h5dataframe

Drop-in replacement for pandas DataFrames that allows to store data on an hdf5 file and manipulate data directly from that h5df file without loading it in memory.

Warning !

This is very much a work in progress, some features might not work yet or cause bugs. Save your data elsewhere before converting it to an H5DataFrame.

If you miss a feature from pandas DataFrames, please fill an issue or feel free to contribute.

Overview

This library provides the H5DataFrame object, replacing the regular pandas.DataFrame.

An H5DataFrame can be created from a pandas.DataFrame or from a dictionnary of (column_name -> column_values).

>>> import pandas as pd
>>> from h5dataframe import H5DataFrame
>>> df = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]}, 
                      index=['r1', 'r2', 'r3'])
>>> hdf = H5DataFrame(df)
>>> hdf
    a  b
r1  1  4
r2  2  5
r3  3  6
[RAM]
[3 rows x 2 columns]

At this point, all the data is still loaded in RAM, as indicated by the second-to-last line. To write the data to an h5df file, use the H5DataFrame.write() method.

>>> hdf.write('path/to/file.h5')
>>> hdf
    a  b
r1  1  4
r2  2  5
r3  3  6
[FILE]
[3 rows x 2 columns]

The H5DataFrame is now backed on an h5df file, only loading data in RAM when requested.

Alternatively, an H5DataFrame can be read directly from an previously created h5df file with the H5DataFrame.read() method.

>>> from h5dataframe import H5Mode
>>> H5DataFrame.read('path/to/file.h5', mode=H5Mode.READ)
    a  b
r1  1  4
r2  2  5
r3  3  6
[FILE]
[3 rows x 2 columns]

The default mode is READ ('r') which creates a read-only H5DataFrame. To modify the data, use mode=H5Mode.READ_WRITE ('r+').

Installation

From pip:

pip install h5dataframe

From source:

git clone git@github.com:Vidium/h5dataframe.git