在 HDFStore 组中存储多个对象

Question

我想在一个 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

Answer 1

试试这个：

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

演示：

In [13]: store = pd.HDFStore('c:/temp/stocks.h5')

In [15]: store['/aaa/bbb'] = df

In [17]: store.groups
Out[17]:
<bound method HDFStore.groups of <class 'pandas.io.pytables.HDFStore'>
File path: c:/temp/stocks.h5
/aaa/bbb            frame        (shape->[3,7])
/stocks             wide_table   (typ->appendable,nrows->6,ncols->3,indexers->[major_axis,minor_axis],dc->[AAPL,ABC,GOOG])>

In [18]: store['/aaa/bbb2'] = df

In [20]: store.items
Out[20]:
<bound method HDFStore.items of <class 'pandas.io.pytables.HDFStore'>
File path: c:/temp/stocks.h5
/aaa/bbb             frame        (shape->[3,7])
/aaa/bbb2            frame        (shape->[3,7])
/stocks              wide_table   (typ->appendable,nrows->6,ncols->3,indexers->[major_axis,minor_axis],dc->[AAPL,ABC,GOOG])>

更新：

In [29]: store.get_node('/aaa')
Out[29]:
/aaa (Group) ''
  children := ['bbb' (Group), 'bbb2' (Group)]

PS AFAIK Pandas 将 key (/aaa/bbb) 视为完整路径

UPDATE2：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])

让我们找到/data_source_1/subdir2中的所有条目：

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']

并且拥有可以轻松选择数据的键：

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]