Python 在HDFStore组中存储多个对象

我想在HDFStore中存储多个对象，但我想通过分组来组织它。大致如下：

import pandas as pd
my_store = pd.HDFStore('my_local_store.h5')
my_store._handle.createGroup('/', 'data_source_1') # this works, but I'm not sure what it does
my_store['/data_source_1']['part-1'] = pd.DataFrame({'b':[1,2,9,2,3,5,2,5]}) # this does not work
my_store['/data_source_1']['part-2'] = pd.DataFrame({'b':[3,8,4,2,5,5,6,1]}) # this does not work either

试试这个：

my_store['/data_source_1/part-1'] = ...

演示：

PS AFAIK Pandas将

键

（

/aaa/bbb

）视为完整路径

更新2:列出商店：

我们有以下商店：

In [19]: store
Out[19]:
<class 'pandas.io.pytables.HDFStore'>
File path: D:\temp\.data\hdf\test_groups.h5
/data_source_1/subdir1/1            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir1/2            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir1/3            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir1/4            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir1/5            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir2/1            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/2            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/3            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/4            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/5            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/6            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/7            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/8            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/9            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])

使用这些键，您可以轻松选择数据：

In [25]: dfs = [store.select(s, where='a > 5') for s in store if s.startswith('/data_source_1/subdir2/')]

In [26]: [len(df) for df in dfs]
Out[26]: [5, 5, 5, 5, 5, 5, 5, 5, 5]

In [29]: dfs = [store.select(s, where='a > 7') for s in store if s.startswith('/data_source_1/subdir2/')]

In [30]: [len(df) for df in dfs]
Out[30]: [4, 4, 4, 4, 4, 4, 4, 4, 4]

---

然后我将如何列出组“aaa”中的所有元素？@mgoldwasser，请参阅更新-这就是您要查找的内容吗？这很有用-如果我想循环遍历子项，我想我可以为我的子项存储中的子项执行以下操作：

[my_store.get（'/data_source_1/'+child）。get_节点（'/data_source__1'）。\u children.keys（）]

但也许有更好的方法…@mgoldwaser，我认为可以做得更简单一些-参见更新2

In [19]: store
Out[19]:
<class 'pandas.io.pytables.HDFStore'>
File path: D:\temp\.data\hdf\test_groups.h5
/data_source_1/subdir1/1            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir1/2            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir1/3            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir1/4            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir1/5            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index])
/data_source_1/subdir2/1            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/2            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/3            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/4            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/5            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/6            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/7            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/8            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])
/data_source_1/subdir2/9            frame_table  (typ->appendable,nrows->10,ncols->3,indexers->[index],dc->[a,b,c])

In [20]: [s for s in store if s.startswith('/data_source_1/subdir2/')]
Out[20]:
['/data_source_1/subdir2/1',
 '/data_source_1/subdir2/2',
 '/data_source_1/subdir2/3',
 '/data_source_1/subdir2/4',
 '/data_source_1/subdir2/5',
 '/data_source_1/subdir2/6',
 '/data_source_1/subdir2/7',
 '/data_source_1/subdir2/8',
 '/data_source_1/subdir2/9']

In [25]: dfs = [store.select(s, where='a > 5') for s in store if s.startswith('/data_source_1/subdir2/')]

In [26]: [len(df) for df in dfs]
Out[26]: [5, 5, 5, 5, 5, 5, 5, 5, 5]

In [29]: dfs = [store.select(s, where='a > 7') for s in store if s.startswith('/data_source_1/subdir2/')]

In [30]: [len(df) for df in dfs]
Out[30]: [4, 4, 4, 4, 4, 4, 4, 4, 4]