用 Pandas 读取 hdf5 数据集
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Reading hdf5 datasets with pandas
提问by hsnee
I'm trying to open a group-less hdf5 file with pandas:
我正在尝试用 Pandas 打开一个无组的 hdf5 文件：
import pandas as pd
foo = pd.read_hdf('foo.hdf5')
but I get an error:
但我收到一个错误：
TypeError: cannot create a storer if the object is not existing nor a value are passed
类型错误：如果对象不存在或传递值，则无法创建存储库
I tried solving this by assigning a key:
我尝试通过分配一个来解决这个问题key：
foo = pd.read_hdf('foo.hdf5','key')
which works if keywas a group, but the file has no groups, but rather several datasets in the highest hdf structure. i.e. the structure of the working file is: Groups --> Datasets, while the structure of the not working file is: Datasets. Both work fine when opening them with h5py, where I would use:
如果key是一个组，则该文件有效，但该文件没有组，而是最高 hdf 结构中的几个数据集。即工作文件的结构是：Groups --> Datasets，而不工作文件的结构是：Datasets。使用 h5py 打开它们时，它们都可以正常工作，我将在其中使用：
f = h5py.File('foo.hdf5','r')
and
和
dset = f['dataset']
to view a dataset. Any ideas how to read this in pandas?
查看数据集。任何想法如何在Pandas中阅读这个？
回答by MaxU
I think you'are confused by different terminology - Pandas's HDF store keyis a full path i.e. Group + DataSet_name...
我认为您对不同的术语感到困惑 - Pandas 的 HDF 存储key是一条完整的路径，即Group + DataSet_name......
demo:
演示：
In [67]: store = pd.HDFStore(r'D:\temp\.data\hdf\test.h5')
In [68]: store.append('dataset1', df)
In [69]: store.append('/group1/sub_group1/dataset2', df)
In [70]: store.groups
Out[70]:
<bound method HDFStore.groups of <class 'pandas.io.pytables.HDFStore'>
File path: D:\temp\.data\hdf\test.h5
/dataset1 frame_table (typ->appendable,nrows->9,ncols->2,indexers->[index])
/group1/sub_group1/dataset2 frame_table (typ->appendable,nrows->9,ncols->2,indexers->[index])>
In [71]: store.items
Out[71]:
<bound method HDFStore.items of <class 'pandas.io.pytables.HDFStore'>
File path: D:\temp\.data\hdf\test.h5
/dataset1 frame_table (typ->appendable,nrows->9,ncols->2,indexers->[index])
/group1/sub_group1/dataset2 frame_table (typ->appendable,nrows->9,ncols->2,indexers->[index])>
In [72]: store.close()
In [73]: x = pd.read_hdf(r'D:\temp\.data\hdf\test.h5', 'dataset1')
In [74]: x.shape
Out[74]: (9, 2)
In [75]: x = pd.read_hdf(r'D:\temp\.data\hdf\test.h5', '/group1/sub_group1/dataset2')
In [76]: x.shape
Out[76]: (9, 2)
