blocks|key|4571361|text|如果它有帮助，当我尝试连接两个数据帧时，我也遇到了这个错误(在撰写本文时，这是除了源代码之外，我在google上唯一能找到的相关命中)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4571362|我不知道这个答案是否会解决OP的问题(因为他/她没有发布足够的信息)，但对我来说，这是因为我试图用列标题(+concat+['A',+'B',+'B',+'C']？)具有列['A',+'B']的dataframe+df2。可以理解的是，这种复制导致大熊猫摇晃了一下。将df1更改为['A',+'B',+'C']+(即删除其中一个重复的列)，一切都会正常工作。|offset|length|style|CODE|4571363|entityMap^0|0|1I|6|1P|K|2E|A|2Z|3|3Q|3|3W|F|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@$D|L|E|M|F|G]|$D|N|E|O|F|G]|$D|P|E|Q|F|G]|$D|R|E|S|F|G]|$D|T|E|U|F|G]|$D|V|E|W|F|G]]|9|@]|A|$]]|$1|H|3|-4|5|6|7|X|8|@]|9|@]|A|$]]]|I|$]]

In case it helps, I have also hit this error when I tried to concatenate two data frames (and as of the time of writing this is the only related hit I can find on google other than the source code). 

I don't know whether this answer would have solved the OP's problem (since he/she didn't post enough information), but for me, this was caused when I tried to <code>concat</code> dataframe <code>df1</code> with columns <code>['A', 'B', 'B', 'C']</code> (see the duplicate column headings?) with dataframe <code>df2</code> with columns <code>['A', 'B']</code>. Understandably the duplication caused pandas to throw a wobbly. Change <code>df1</code> to <code>['A', 'B', 'C']</code> (i.e. drop one of the duplicate columns) and everything works fine.

blocks|key|4571401|text|我最近也收到了这条消息，我发现像上面的用户@jason和@user3805082一样，在我试图concat的数百个数据帧中，有几个列重复，每个数据帧都有几十个神秘的变量名。手动搜索重复项是不现实的。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4571402|如果其他人有同样的问题，我写了下面的函数，它可能会有所帮助。|4571403|def+duplicated_varnames(df):
++++"""Return+a+dict+of+all+variable+names+that+
++++are+duplicated+in+a+given+dataframe."""
++++repeat_dict+=+{}
++++var_list+=+list(df)+#+list+of+varnames+as+strings
++++for+varname+in+var_list:
++++++++#+make+a+list+of+all+instances+of+that+varname
++++++++test_list+=+[v+for+v+in+var_list+if+v+==+varname]+
++++++++#+if+more+than+one+instance,+report+duplications+in+repeat_dict
++++++++if+len(test_list)+>+1:+
++++++++++++repeat_dict[varname]+=+len(test_list)
++++return+repeat_dict|code-block|syntax|javascript|4571404|然后，您可以迭代该字典，以报告有多少重复的变量，删除重复的变量，或以某种系统的方式重命名它们。|4571405|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/users/1744744/jason|1|https://stackoverflow.com/users/3805082/user3805082^0|1B|6|L|6|0|S|C|1|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@$9|Z|A|10|B|C]]|D|@$9|11|A|12|1|13]|$9|14|A|15|1|16]]|E|$]]|$1|F|3|G|5|6|7|17|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|18|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|19|8|@]|D|@]|E|$]]|$1|O|3|-4|5|6|7|1A|8|@]|D|@]|E|$]]]|P|$Q|$5|R|S|T|E|$U|V]]|W|$5|R|S|T|E|$U|X]]]]

I recently got this message, too, and I found like user <a href="https://stackoverflow.com/users/1744744/jason">@jason</a> and <a href="https://stackoverflow.com/users/3805082/user3805082">@user3805082</a> above that I had duplicate columns in several of the hundreds of dataframes I was trying to <code>concat</code>, each with dozens of enigmatic varnames. Manually searching for duplicates was not practical.

In case anyone else has the same problem, I wrote the following function which might help out. 

<pre><code>def duplicated_varnames(df):
 """Return a dict of all variable names that 
 are duplicated in a given dataframe."""
 repeat_dict = {}
 var_list = list(df) # list of varnames as strings
 for varname in var_list:
 # make a list of all instances of that varname
 test_list = [v for v in var_list if v == varname] 
 # if more than one instance, report duplications in repeat_dict
 if len(test_list) &gt; 1: 
 repeat_dict[varname] = len(test_list)
 return repeat_dict
</code></pre>

Then you can iterate over that dict to report how many duplicates there are, delete the duplicated variables, or rename them in some systematic way.

blocks|key|65079|text|编写了一个小函数来连接重复的列名。函数关心排序如果原始数据帧未排序，则输出将是排序的数据帧。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|65080|def+concat_duplicate_columns(df):
++++dupli+=+{}
++++#+populate+dictionary+with+column+names+and+count+for+duplicates+
++++for+column+in+df.columns:
++++++++dupli[column]+=+dupli[column]+%2B+1+if+column+in+dupli.keys()+else+1
++++#+rename+duplicated+keys+with+°°°+number+suffix
++++for+key,+val+in+dict(dupli).items():
++++++++del+dupli[key]
++++++++if+val+>+1:
++++++++++++for+i+in+range(val):
++++++++++++++++dupli[key%2B'°°°'%2Bstr(i)]+=+val
++++++++else:+dupli[key]+=+1
++++#+rename+columns+so+that+we+can+now+access+abmigous+column+names
++++#+sorting+in+dict+is+the+same+as+in+original+table
++++df.columns+=+dupli.keys()
++++#+for+each+duplicated+column+name
++++for+i+in+set(re.sub('°°°(.*)','',j)+for+j+in+dupli.keys()+if+'°°°'+in+j):
++++++++i+=+str(i)
++++++++#+for+each+duplicate+of+a+column+name
++++++++for+k+in+range(dupli[i%2B'°°°0']-1):
++++++++++++#+concatenate+values+in+duplicated+columns
++++++++++++df[i%2B'°°°0']+=+df[i%2B'°°°0'].astype(str)+%2B+df[i%2B'°°°'%2Bstr(k%2B1)].astype(str)
++++++++++++#+Drop+duplicated+columns+from+which+we+have+aquired+data
++++++++++++df+=+df.drop(i%2B'°°°'%2Bstr(k%2B1),+1)
++++#+resort+column+names+for+proper+mapping
++++df+=+df.reindex_axis(sorted(df.columns),+axis+=+1)
++++#+rename+columns
++++df.columns+=+sorted(set(re.sub('°°°(.*)','',i)+for+i+in+dupli.keys()))
++++return+df|code-block|syntax|javascript|65081|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Wrote a small function to concatenate duplicated column names.
Function cares about sorting if original dataframe is unsorted, the output will be a sorted one.

<pre><code>def concat_duplicate_columns(df):
 dupli = {}
 # populate dictionary with column names and count for duplicates 
 for column in df.columns:
 dupli[column] = dupli[column] + 1 if column in dupli.keys() else 1
 # rename duplicated keys with °°° number suffix
 for key, val in dict(dupli).items():
 del dupli[key]
 if val &gt; 1:
 for i in range(val):
 dupli[key+'°°°'+str(i)] = val
 else: dupli[key] = 1
 # rename columns so that we can now access abmigous column names
 # sorting in dict is the same as in original table
 df.columns = dupli.keys()
 # for each duplicated column name
 for i in set(re.sub('°°°(.*)','',j) for j in dupli.keys() if '°°°' in j):
 i = str(i)
 # for each duplicate of a column name
 for k in range(dupli[i+'°°°0']-1):
 # concatenate values in duplicated columns
 df[i+'°°°0'] = df[i+'°°°0'].astype(str) + df[i+'°°°'+str(k+1)].astype(str)
 # Drop duplicated columns from which we have aquired data
 df = df.drop(i+'°°°'+str(k+1), 1)
 # resort column names for proper mapping
 df = df.reindex_axis(sorted(df.columns), axis = 1)
 # rename columns
 df.columns = sorted(set(re.sub('°°°(.*)','',i) for i in dupli.keys()))
 return df
</code></pre>

blocks|key|4571467|text|对于要合并的所有df，您需要具有相同的标头名称。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4571468|例如，使用以下命令：|4571469|headername+=列表(Df)|4571470|Data+=Data.filter(标题名)|4571471|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

You need to have the same header names for all the df you want to concat.

Do it for example with :

headername = list(df)

Data = Data.filter(headername)

blocks|key|65144|text|错误是具有重复列的结果。使用以下函数可删除重复函数，而不会影响数据。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|65145|def+duplicated_varnames(df):
++++repeat_dict+=+{}
++++var_list+=+list(df)+#+list+of+varnames+as+strings
++++for+varname+in+var_list:
++++++++test_list+=+[v+for+v+in+var_list+if+v+==+varname]+
++++++++if+len(test_list)+>+1:+
++++++++++++repeat_dict[varname]+=+len(test_list)
++++++++if+len(repeat_dict)>0:
++++++++++++df+=+df.loc[:,~df.columns.duplicated()]
++++return+df|code-block|syntax|javascript|65146|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Error is result of having duplicate columns. Use following function in order to remove duplicate function without impacting data.
<pre><code>def duplicated_varnames(df):
 repeat_dict = {}
 var_list = list(df) # list of varnames as strings
 for varname in var_list:
 test_list = [v for v in var_list if v == varname] 
 if len(test_list) &gt; 1: 
 repeat_dict[varname] = len(test_list)
 if len(repeat_dict)&gt;0:
 df = df.loc[:,~df.columns.duplicated()]
 return df
</code></pre>

blocks|key|65177|text|我收到了ValueError:将数据帧添加到一起时平面形状不对齐。我试图在Excel工作表上循环，并在清理后将它们压缩在一起。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|65178|错误被抛出，因为它们是多个none列，我用以下代码删除了这些列：|65179|在堆栈溢出上找到df+=+df.loc:，df.columns.notnull()+#|65180|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

I was receiving the ValueError: Plan shapes are not aligned when adding dataframes together. I was trying to loop over Excel sheets and after cleaning concacting them together.
The error was being raised as their were multiple none columns which I dropped with the code below:
df = df.loc[:, df.columns.notnull()] # found on stackoverflow

In pandas, I am attempting to concatenate a set of dataframes and I am getting this error:
<pre><code>ValueError: Plan shapes are not aligned
</code></pre>
My understanding of <code>.concat()</code> is that it will join where columns are the same, but for those that it can't find it will fill with NA. This doesn't seem to be the case here.
Here's the concat statement:
<pre><code>dfs = [npo_jun_df, npo_jul_df,npo_may_df,npo_apr_df,npo_feb_df]
alpha = pd.concat(dfs)
</code></pre>

Pandas concat yields ValueError: Plan shapes are not aligned

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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在pandas中，我尝试连接一组数据帧，并收到以下错误：ValueError: Plan shapes are not aligned我对.concat()的理解是，它会在列相同的地方加入，但对于那些找不到的列，它会用NA填充。这里似乎不是这样。下面是concat语句：dfs = [npo_jun_df, npo_ju...

问Pandas concat产生ValueError:平面形状未对齐
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问Pandas concat产生ValueError:平面形状未对齐EN