使用h5py保存pandas DataFrame与其他HDF5读卡器的互操作性 [英] Save pandas DataFrame using h5py for interoperabilty with other hdf5 readers

问题描述

这是一个示例数据框:

import pandas as pd

NaN = float('nan')
ID = [1, 2, 3, 4, 5, 6, 7]
A = [NaN, NaN, NaN, 0.1, 0.1, 0.1, 0.1]
B = [0.2, NaN, 0.2, 0.2, 0.2, NaN, NaN]
C = [NaN, 0.5, 0.5, NaN, 0.5, 0.5, NaN]
columns = {'A':A, 'B':B, 'C':C}
df = pd.DataFrame(columns, index=ID)
df.index.name = 'ID'
print(df)

      A    B    C
ID               
1   NaN  0.2  NaN
2   NaN  NaN  0.5
3   NaN  0.2  0.5
4   0.1  0.2  NaN
5   0.1  0.2  0.5
6   0.1  NaN  0.5
7   0.1  NaN  NaN

我知道pandas具有基于pytables的HDFStore，这是有效序列化/反序列化数据帧的简便方法.但是，使用阅读器h5py或matlab直接加载这些数据集并不容易.如何使用h5py保存数据帧，以便可以使用其他hdf5阅读器轻松加载回该数据帧?

I know that pandas has the pytables based HDFStore, which is an easy way to efficiently serialize/deserialize a data frame. But those datasets are not very easy to load directly using a reader h5py or matlab. How can I save a data frame using h5py, so that I can easily load it back using another hdf5 reader?

推荐答案

pandas HDFStore格式是标准的HDF5，只是有关如何解释元数据的约定.文档位于此处

The pandas HDFStore format is standard HDF5, with just a convention for how to interpret the meta-data. Docs are here

In [54]: df.to_hdf('test.h5','df',mode='w',format='table',data_columns=True)

In [55]: h = h5py.File('test.h5')

In [56]: h['df']['table']
Out[56]: <HDF5 dataset "table": shape (7,), type "|V32">

In [64]: h['df']['table'][:]
Out[64]: 
array([(1, nan, 0.2, nan), (2, nan, nan, 0.5), (3, nan, 0.2, 0.5),
       (4, 0.1, 0.2, nan), (5, 0.1, 0.2, 0.5), (6, 0.1, nan, 0.5),
       (7, 0.1, nan, nan)], 
      dtype=[('index', '<i8'), ('A', '<f8'), ('B', '<f8'), ('C', '<f8')])


In [57]: h['df']['table'].attrs.items()
Out[57]: 
[(u'CLASS', 'TABLE'),
 (u'VERSION', '2.7'),
 (u'TITLE', ''),
 (u'FIELD_0_NAME', 'index'),
 (u'FIELD_1_NAME', 'A'),
 (u'FIELD_2_NAME', 'B'),
 (u'FIELD_3_NAME', 'C'),
 (u'FIELD_0_FILL', 0),
 (u'FIELD_1_FILL', 0.0),
 (u'FIELD_2_FILL', 0.0),
 (u'FIELD_3_FILL', 0.0),
 (u'index_kind', 'integer'),
 (u'A_kind', "(lp1\nS'A'\na."),
 (u'A_meta', 'N.'),
 (u'A_dtype', 'float64'),
 (u'B_kind', "(lp1\nS'B'\na."),
 (u'B_meta', 'N.'),
 (u'B_dtype', 'float64'),
 (u'C_kind', "(lp1\nS'C'\na."),
 (u'C_meta', 'N.'),
 (u'C_dtype', 'float64'),
 (u'NROWS', 7)]

In [58]: h.close()

任何HDF5阅读器都可以完全读取数据.对某些元数据进行了腌制，因此必须小心.

The data will be completely readable in any HDF5 reader. Some of the meta-data is pickled, so care must be taken.

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