Question

大家好，并提前致谢。

我正在尝试定期将财务数据存储到数据库以供以后查询。我正在使用Pandas进行几乎所有的数据编码。我想将我创建的数据帧附加到HDF数据库中。我将csv读入数据帧并按时间戳索引。和DataFrame看起来像：

<class 'pandas.core.frame.DataFrame'>
Int64Index: 900 entries, 1378400701110 to 1378410270251
Data columns (total 23 columns):
....
...Columns with numbers of non-null values....
.....
dtypes: float64(19), int64(4)

store = pd.HDFStore('store1.h5')
store.append('df', df)
print store

<class 'pandas.io.pytables.HDFStore'>
File path: store1.h5
/df            frame_table  (typ->appendable,nrows->900,ncols->23,indexers->[index])

但是当我尝试对商店做任何事情时，

print store['df']
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python2.7/dist-packages/pandas/io/pytables.py", line 289,  in          __getitem__
return self.get(key)
File "/usr/local/lib/python2.7/dist-packages/pandas/io/pytables.py", line 422, in get
return self._read_group(group)
File "/usr/local/lib/python2.7/dist-packages/pandas/io/pytables.py", line 930, in                _read_group
return s.read(**kwargs)
File "/usr/local/lib/python2.7/dist-packages/pandas/io/pytables.py", line 3175, in read
mgr = BlockManager([block], [cols_, index_])
File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 1007, in __init__
self._set_ref_locs(do_refs=True)
File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 1117, in _set_ref_locs
"does not have _ref_locs set" % (block,labels))
AssertionError: cannot create BlockManager._ref_locs because block 
[FloatBlock:   [LastTrade, Bid1, Bid1Volume,....., Ask5Volume], 19 x 900, dtype float64] 
with duplicate items 
[Index([u'LastTrade', u'Bid1', u'Bid1Volume',..., u'Ask5Volume'], dtype=object)] 
does not have _ref_locs set

我想我的索引做错了，我对此很新，并且知之甚少。

编辑：

数据框架结构如下：

columns = ['TimeStamp', 'LastTrade', 'Bid1', 'Bid1Volume', 'Bid1', 'Bid1Volume',    'Bid2', 'Bid2Volume', 'Bid3', 'Bid3Volume', 'Bid4', 'Bid4Volume', 
       'Bid5', 'Bid5Volume', 'Ask1', 'Ask1Volume', 'Ask2', 'Ask2Volume', 'Ask3', 'Ask3Volume', 'Ask4', 'Ask4Volume', 'Ask5', 'Ask5Volume']

df = pd.read_csv('/20130905.csv', names=columns, index_col=[0])

df.head（）看起来像：

<class 'pandas.core.frame.DataFrame'>
Int64Index: 5 entries, 1378400701110 to 1378400703105
Data columns (total 21 columns):
LastTrade     5  non-null values
Bid1          5  non-null values
Bid1Volume    5  non-null values
Bid1          5  non-null values
.................values
Ask4          5  non-null values
Ask4Volume    5  non-null values
dtypes: float64(17), int64(4)

打印内容的列太多了。但是例如：

print df['LastTrade'].iloc[10]
LastTrade    1.31202
Name: 1378400706093, dtype: float64

和熊猫版：

>>> pd.__version__
'0.12.0'

任何想法都会非常感激，再次感谢你。

Answer 1

您确实有重复的“Bid1”和“Bid1Volume”列吗？

不相关，但您还应将索引设置为日期时间索引

import pandas as pd
df.index = pd.to_datetime(df.index,unit='ms')

这是一个错误，因为重复列交叉dtypes（不是什么大问题但未被发现。）

最容易就是没有重复的列。

将在0.13中修复，请参见此处：https://github.com/pydata/pandas/pull/4768

Pandas HDFStore重复项错误

1 个答案: