blocks|key|349647|text|在读取和写入csv文件时，通常应该保留列顺序，但是如果由于某种原因，列顺序不是您想要的顺序，则可以在to_csv中使用columns关键字参数。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|349648|例如，如果您有一个包含a、b、c、d列的csv：|349649|data+=+pd.read_csv(filename)
data.to_csv(filename,+columns=['a',+'b',+'c',+'d'])|code-block|syntax|javascript|349650|entityMap^0|1E|6|1N|7|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]|$9|R|A|S|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|T|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|U|8|@]|D|@]|E|$K|L]]|$1|M|3|-4|5|6|7|V|8|@]|D|@]|E|$]]]|N|$]]

The column order should generally be preserved when reading and then writing a csv file like that, but if for some reason they are not in the order you want you can use the <code>columns</code> keyword argument in <code>to_csv</code>.

For example, if you have a csv with columns a, b, c, d:

<pre><code>data = pd.read_csv(filename)
data.to_csv(filename, columns=['a', 'b', 'c', 'd'])
</code></pre>

blocks|key|349702|text|在当前版本的Pandas+('0.11.0')中似乎有一个bug，这意味着Matti+John的答案将不起作用。如果指定要写入文件的列，这些列将按字母顺序写入，但只需根据cols中的列表重新标记即可。例如，下面的代码：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|349703|import+pandas
dfdict={}
dfdict["a"]=[1,2,3,4]
dfdict["b"]=[5,6,7,8]
dfdict["c"]=[9,10,11,12]
df=pandas.DataFrame(dfdict)
df.to_csv("dfTest.txt","\t",header=True,cols=["b","a","c"])|code-block|syntax|javascript|349704|导致此(不正确)输出：|349705|++++b+++a+++c
0+++1+++5+++9
1+++2+++6+++10
2+++3+++7+++11
3+++4+++8+++12|349706|您可以通过执行以下命令来检查已安装的pandas的版本：|349707|pandas.version.version|349708|here是to_csv的文档|offset|length|349709|实际上，这似乎是一个已知的错误，将在即将发布的版本(0.11.1)中修复：|349710|https://github.com/pydata/pandas/issues/3489|349711|更新:目前还没有新的pandas版本，但这里描述了一个解决方法，它不需要使用不同版本的pandas：|349712|github.com/pydata/pandas/issues/3454|349713|因此，将上述代码块中的最后一行更改为以下内容将正常工作：|349714|df.to_csv("dfTest.txt","\t",header=True,cols=["b","a","c"],+engine='python')|349715|UPDATE似乎参数"cols“已被重命名为"columns”，并且参数"engine“在最近的pandas版本中已被弃用(不再可用)。此外，此错误已在版本0.19.0中修复。|349716|entityMap|0|LINK|mutability|MUTABLE|url|http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html|1|2|https://github.com/pydata/pandas/issues/3454^0|0|0|0|0|0|0|0|4|0|0|0|0|18|1|0|0|0|10|2|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1H|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|1I|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|1J|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|1K|8|@]|9|@]|A|$E|F]]|$1|K|3|L|5|6|7|1L|8|@]|9|@]|A|$]]|$1|M|3|N|5|D|7|1M|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|1N|8|@]|9|@$Q|1O|R|1P|1|1Q]]|A|$]]|$1|S|3|T|5|6|7|1R|8|@]|9|@]|A|$]]|$1|U|3|V|5|6|7|1S|8|@]|9|@$Q|1T|R|1U|1|1V]]|A|$]]|$1|W|3|X|5|6|7|1W|8|@]|9|@]|A|$]]|$1|Y|3|Z|5|6|7|1X|8|@]|9|@$Q|1Y|R|1Z|1|20]]|A|$]]|$1|10|3|11|5|6|7|21|8|@]|9|@]|A|$]]|$1|12|3|13|5|D|7|22|8|@]|9|@]|A|$E|F]]|$1|14|3|15|5|6|7|23|8|@]|9|@]|A|$]]|$1|16|3|-4|5|6|7|24|8|@]|9|@]|A|$]]]|17|$18|$5|19|1A|1B|A|$1C|1D]]|1E|$5|19|1A|1B|A|$1C|V]]|1F|$5|19|1A|1B|A|$1C|1G]]]]

There appears to be a bug in the current version of Pandas ('0.11.0'), which means that Matti John's answer will not work. If you specify columns for writing to file, they are written in alphabetical order, but simply relabelled according to the list in cols. For example, this code:

<pre><code>import pandas
dfdict={}
dfdict["a"]=[1,2,3,4]
dfdict["b"]=[5,6,7,8]
dfdict["c"]=[9,10,11,12]
df=pandas.DataFrame(dfdict)
df.to_csv("dfTest.txt","\t",header=True,cols=["b","a","c"])
</code></pre>

results in this (incorrect) output:

<pre><code> b a c
0 1 5 9
1 2 6 10
2 3 7 11
3 4 8 12
</code></pre>

You can check which version of pandas you have installed by executing:

<pre><code>pandas.version.version
</code></pre>

Documentation for to_csv is <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html" rel="noreferrer">here</a>

Actually, it seems that this is a known bug and will be fixed in an upcoming release (0.11.1):

<a href="https://github.com/pydata/pandas/issues/3489" rel="noreferrer">https://github.com/pydata/pandas/issues/3489</a>

UPDATE: There still hasn't been a new release of pandas, but there is a workaround described here, which doesn't require using a different version of pandas: 

<a href="https://github.com/pydata/pandas/issues/3454" rel="noreferrer">github.com/pydata/pandas/issues/3454</a> 

So changing the last line in the block of code above to the following will work correctly: 

<pre><code>df.to_csv("dfTest.txt","\t",header=True,cols=["b","a","c"], engine='python')
</code></pre>

UPDATE it seems that the argument "cols" has been renamed to "columns" and that the argument "engine" is deprecated (no longer available) in recent versions of pandas. Also, this bug is fixed in version 0.19.0.

blocks|key|349721|text|另一种解决方法是执行以下操作：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|349722|import+pandas+as+pd
data+=+pd.read_csv(filename)
data2+=+df[['A','B','C']]++#put+'A'+'B'+'C'+in+the+desired+order
data2.to_csv(filename)|code-block|syntax|javascript|349723|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|$]]

Another workaround is to do this:

<pre><code>import pandas as pd
data = pd.read_csv(filename)
data2 = df[['A','B','C']] #put 'A' 'B' 'C' in the desired order
data2.to_csv(filename)
</code></pre>

Is there a way to preserve the order of the columns in a csv file when read and the write with Python Pandas? For example, in this code

<pre><code>import pandas as pd

data = pd.read_csv(filename)
data.to_csv(filename)
</code></pre>

the output files might be different because the columns are not preserved.

Preserving column order in Python Pandas DataFrame

Python

在使用Python Pandas进行读取和写入时，有没有办法保持csv文件中列的顺序？例如，在下面的代码中import pandas as pddata = pd.read_csv(filename)data.to_csv(filename)输出文件可能会有所不同，因为列没有保留。

问在Python Pandas DataFrame中保留列顺序
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