在没有列名的pandas中合并两个数据帧(对pandas来说是新的)

概述简短说明： 如果数据中有重复的列名,请确保在读取文件时重命名一列. 如果您的数据中有NaN等,请删除它们. 然后使用下面的正确答案合并. 可能是一个非常简单的问题. 我使用pandas.read_csv()读入了两个数据集. 我的数据在两个单独的csv中. 使用以下代码： import mibian import pandas as pd underlying 简短说明：

如果数据中有重复的列名,请确保在读取文件时重命名一列.

如果您的数据中有NaN等,请删除它们.

然后使用下面的正确答案合并.

可能是一个非常简单的问题.

我使用pandas.read_csv()读入了两个数据集.

我的数据在两个单独的csv中.

使用以下代码：

import mibian        import pandas as pd        underlying = pd.read_csv("txt1.csv",names=['dt1','price']);        options = pd.read_csv("txt2.txt",names=['dt2','ticker','maturity','strike','cP','px','yIEld','rF','T','rlzd10']);        merged = underlying.merge(options,left_on='dt1',right_on='dt2');

我的两个数据头看起来像这样：

>>> underlying.head();          0         10  20040326  3.5799871  20040329  3.6904942  20040330  3.7552473  20040331  3.7193734  20040401  3.728671

和

>>> options.head();         0     1         2     3     4      5     6   7      8         9                100  20130628  SVXY  20130817  32.5  call  39.22  32.5   0  0.005  0.136986   0.411224

所以我在任一数据集上的列0是我要合并的键,我想保留两个结果集中的所有数据.

我该怎么做呢？我在网上找到的所有例子都需要密钥,但我的结果中没有.

但是在连接上我得到以下错误：

Traceback (most recent call last):                              file "<stdin>",line 1,in <module>                              file "/Applications/Spyder.app/Contents/Resources/lib/python2.7/spyderlib/Widgets/externalshell/sitecustomize.py",line 540,in runfile                                execfile(filename,namespace)                              file "/Users/jasonmellone/.spyder2/.temp.py",line 12,in <module>                                merged = underlying.merge(options,right_on='dt2',how='outer');                              file "/library/Python/2.7/site-packages/pandas-0.13.0-py2.7-macosx-10.9-intel.egg/pandas/core/frame.py",line 3723,in merge                                suffixes=suffixes,copy=copy)                              file "/library/Python/2.7/site-packages/pandas-0.13.0-py2.7-macosx-10.9-intel.egg/pandas/tools/merge.py",line 40,in merge                                return op.get_result()                              file "/library/Python/2.7/site-packages/pandas-0.13.0-py2.7-macosx-10.9-intel.egg/pandas/tools/merge.py",line 197,in get_result                                result_data = join_op.get_result()                              file "/library/Python/2.7/site-packages/pandas-0.13.0-py2.7-macosx-10.9-intel.egg/pandas/tools/merge.py",line 722,in get_result                                return BlockManager(result_blocks,self.result_axes)                              file "/library/Python/2.7/site-packages/pandas-0.13.0-py2.7-macosx-10.9-intel.egg/pandas/core/internals.py",line 1954,in __init__                                self._set_ref_locs(do_refs=True)                              file "/library/Python/2.7/site-packages/pandas-0.13.0-py2.7-macosx-10.9-intel.egg/pandas/core/internals.py",line 2091,in _set_ref_locs                                'have _ref_locs set' % (block,labels))                            AssertionError: Cannot create BlockManager._ref_locs because block [IntBlock: [dt1],1 x 372145,dtype: int64] with duplicate items [Index([u'dt1',u'price',u'dt2',u'ticker',u'maturity',u'strike',u'cP',u'px',u'yIEld',u'rF',u'T',u'rlzd10'],dtype='object')] does not have _ref_locs set

我搜索了我的数据集,没有重复.

谢谢！

解决方法 您仍然可以在列上合并：

merged = underlying.merge(options,left_on='0',right_on='0')

这将执行内部合并,因此只有两个数据集的交集,即如果你想要所有值,那么两列中的值都存在于哪里,然后指定外部：

merged = underlying.merge(options,right_on='0',how='outer')In [10]:  merged = underlying.merge(options,how='outer')mergedOut[10]:          0       1_x   1_y         2     3     4      5     6   7      8  
df = pd.read_csv('data.csv',names=['ID','Price'])
  20040326  3.579987   NaN       NaN   NaN   NaN    NaN   NaN NaN    NaN   1  20040329  3.690494   NaN       NaN   NaN   NaN    NaN   NaN NaN    NaN   2  20040330  3.755247   NaN       NaN   NaN   NaN    NaN   NaN NaN    NaN   3  20040331  3.719373   NaN       NaN   NaN   NaN    NaN   NaN NaN    NaN   4  20040401  3.728671   NaN       NaN   NaN   NaN    NaN   NaN NaN    NaN   5  20130628       NaN  SVXY  20130817  32.5  call  39.22  32.5   0  0.005             9        10  0       NaN       NaN  1       NaN       NaN  2       NaN       NaN  3       NaN       NaN  4       NaN       NaN  5  0.136986  0.411224  [6 rows x 12 columns]

您必须重命名或移动上面发生冲突的列1_x和1_y.

最好将列重命名为事先合情合理的东西.
阅读csv时,您可以传递列名列表：

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