blocks|key|271622|text|如果可能，请从电子表格应用程序另存为CSV，然后使用pandas.read_csv()。IIRC，一个'ods‘电子表格文件实际上是一个XML文件，它也包含相当多的格式化信息。因此，如果是关于表格数据，首先将原始数据提取到一个中间文件(在本例中为CSV)，然后可以使用其他程序解析该文件，比如Python/pandas。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|271623|entityMap^0|Q|H|0^^$0|@$1|2|3|4|5|6|7|H|8|@$9|I|A|J|B|C]]|D|@]|E|$]]|$1|F|3|-4|5|6|7|K|8|@]|D|@]|E|$]]]|G|$]]

If possible, save as CSV from the spreadsheet application and then use <code>pandas.read_csv()</code>. IIRC, an 'ods' spreadsheet file actually is an XML file which also contains quite some formatting information. So, if it's about tabular data, extract this raw data first to an intermediate file (CSV, in this case), which you can then parse with other programs, such as Python/pandas.

blocks|key|271640|text|另一种选择：read-ods-with-odfpy。此模块接受OpenDocument电子表格作为输入，并返回一个列表，从中可以创建一个DataFrame。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|271641|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/marcoconti83/read-ods-with-odfpy^0|6|J|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Another option: <a href="https://github.com/marcoconti83/read-ods-with-odfpy" rel="nofollow noreferrer">read-ods-with-odfpy</a>. This module takes an OpenDocument Spreadsheet as input, and returns a list, out of which a DataFrame can be created.

blocks|key|55230|text|在Pandas+(+xls和xlsx)中支持读取Excel文件，请参阅read_excel命令。可以使用OpenOffice将电子表格另存为xlsx。转换也可以在命令行上自动完成，显然是使用convert-to+command+line+parameter。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|55231|从xlsx读取数据可以避免在第一次转换为CSV时可能遇到的一些问题(日期格式、数字格式、unicode)。|55232|entityMap|0|LINK|mutability|MUTABLE|url|http://pandas.pydata.org/pandas-docs/stable/io.html#excel-files|1|http://ask.libreoffice.org/en/question/2641/convert-to-command-line-parameter/^0|Z|A|0|2N|X|1|0|0^^$0|@$1|2|3|4|5|6|7|P|8|@]|9|@$A|Q|B|R|1|S]|$A|T|B|U|1|V]]|C|$]]|$1|D|3|E|5|6|7|W|8|@]|9|@]|C|$]]|$1|F|3|-4|5|6|7|X|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]|N|$5|I|J|K|C|$L|O]]]]

There is support for reading Excel files in Pandas (both xls and xlsx), see the <a href="http://pandas.pydata.org/pandas-docs/stable/io.html#excel-files" rel="nofollow">read_excel</a> command. You can use OpenOffice to save the spreadsheet as xlsx. The conversion can also be done automatically on the command line, apparently, using the <a href="http://ask.libreoffice.org/en/question/2641/convert-to-command-line-parameter/" rel="nofollow">convert-to command line parameter</a>.

Reading the data from xlsx avoids some of the issues (date formats, number formats, unicode) that you may run into when you convert to CSV first.

blocks|key|55301|text|编辑:幸运的是，如果你可以更新到最新的Pandas版本，下面的答案现在已经过时了。如果您仍然希望使用Pandas版本的数据，并且仅在需要时才从ODS更新它，请继续阅读。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|55302|55303|似乎答案是否定的！我会将读取ODS的工具描述为仍然参差不齐。如果您使用的是POSIX，那么在使用Pandas非常好的xlsx导入工具之前动态导出到xlsx的策略可能是一种选择：|55304|unoconv+-f+xlsx+-o+tmp.xlsx+myODSfile.ods+|code-block|syntax|javascript|55305|总之，我的代码如下所示：|55306|import+pandas+as+pd
import+os
if+fileOlderThan('tmp.xlsx','myODSfile.ods'):
++++os.system('unoconv+-f+xlsx+-o+tmp.xlsx+myODSfile.ods+')
xl_file+=+pd.ExcelFile('tmp.xlsx')
dfs+=+{sheet_name:+xl_file.parse(sheet_name)+
++++++++++for+sheet_name+in+xl_file.sheet_names}
df=dfs['Sheet1']|55307|这里，fileOlderThan()是一个函数(请参阅http://github.com/cpbl/cpblUtilities)，如果tmp.xlsx不存在或比.ods文件旧，则该函数返回true。|offset|length|55308|entityMap|0|LINK|mutability|MUTABLE|url|http://github.com/cpbl/cpblUtilities^0|0|0|0|0|0|0|R|10|0|0^^$0|@$1|2|3|4|5|6|7|Z|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|10|8|@]|9|@]|A|$]]|$1|C|3|D|5|6|7|11|8|@]|9|@]|A|$]]|$1|E|3|F|5|G|7|12|8|@]|9|@]|A|$H|I]]|$1|J|3|K|5|6|7|13|8|@]|9|@]|A|$]]|$1|L|3|M|5|G|7|14|8|@]|9|@]|A|$H|I]]|$1|N|3|O|5|6|7|15|8|@]|9|@$P|16|Q|17|1|18]]|A|$]]|$1|R|3|-4|5|6|7|19|8|@]|9|@]|A|$]]]|S|$T|$5|U|V|W|A|$X|Y]]]]

<h2>Edit: Happily, this answer below is now out of date, if you can update to a recent Pandas version.
If you'd still like to work from a Pandas version of your data, and update it from ODS only when needed, read on.</h2>
<hr />
It seems the answer is No!
And I would characterize the tools to read in ODS still ragged.
If you're on POSIX, maybe the strategy of exporting to xlsx on the fly before using Pandas' very nice importing tools for xlsx is an option:
<pre><code>unoconv -f xlsx -o tmp.xlsx myODSfile.ods 
</code></pre>
Altogether, my code looks like:
<pre><code>import pandas as pd
import os
if fileOlderThan('tmp.xlsx','myODSfile.ods'):
 os.system('unoconv -f xlsx -o tmp.xlsx myODSfile.ods ')
xl_file = pd.ExcelFile('tmp.xlsx')
dfs = {sheet_name: xl_file.parse(sheet_name) 
 for sheet_name in xl_file.sheet_names}
df=dfs['Sheet1']
</code></pre>
Here fileOlderThan() is a function (see <a href="http://github.com/cpbl/cpblUtilities" rel="nofollow noreferrer">http://github.com/cpbl/cpblUtilities</a>) which returns true if tmp.xlsx does not exist or is older than the .ods file.

blocks|key|271780|text|如果你只有几个.ods文件要读，我可以在openoffice中打开它，并将其另存为excel文件。如果您有很多文件，可以使用Linux中的unoconv+command以编程方式将.ods文件转换为.xls+(with+bash)。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|271781|然后用pd.read_excel('filename.xls')就可以很容易地读入它|271782|entityMap|0|LINK|mutability|MUTABLE|url|https://linuxconfig.org/how-to-convert-documents-between-libreoffice-and-microsoft-office-file-formats-on-linux|1|https://stackoverflow.com/questions/4256107/running-bash-commands-in-python^0|1X|7|1X|F|0|2X|9|1|0|3|T|0^^$0|@$1|2|3|4|5|6|7|R|8|@$9|S|A|T|B|C]]|D|@$9|U|A|V|1|W]|$9|X|A|Y|1|Z]]|E|$]]|$1|F|3|G|5|6|7|10|8|@$9|11|A|12|B|C]]|D|@]|E|$]]|$1|H|3|-4|5|6|7|13|8|@]|D|@]|E|$]]]|I|$J|$5|K|L|M|E|$N|O]]|P|$5|K|L|M|E|$N|Q]]]]

If you only have a few .ods files to read, I would just open it in openoffice and save it as an excel file. If you have a lot of files, you could use the <a href="https://linuxconfig.org/how-to-convert-documents-between-libreoffice-and-microsoft-office-file-formats-on-linux" rel="nofollow noreferrer"><code>unoconv</code> command</a> in Linux to convert the .ods files to .xls programmatically (<a href="https://stackoverflow.com/questions/4256107/running-bash-commands-in-python">with bash</a>)

Then it's really easy to read it in with <code>pd.read_excel('filename.xls')</code>

blocks|key|271813|text|我用熊猫read_clipboard已经很幸运了。选择单元格，然后从excel或opendocument复制。在python中，运行以下命令。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|271814|import+pandas+as+pd
data+=+pd.read_clipboard()|code-block|syntax|javascript|271815|熊猫将基于复制的细胞做好工作。|271816|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

I've had good luck with pandas read_clipboard.
Selecting cells and then copy from excel or opendocument.
In python run the following.

<pre><code>import pandas as pd
data = pd.read_clipboard()
</code></pre>

Pandas will do a good job based on the cells copied.

blocks|key|271877|text|在很大程度上基于davidovitch的回答(谢谢)，我编写了一个读入.ods文件并返回DataFrame的package。它不是pandas本身的完整实现，例如his+PR，但它提供了一个简单的read_ods函数来完成这项工作。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|271878|您可以使用pip+install+pandas_ods_reader安装它。还可以指定文件是否包含标题行，以及指定自定义列名。|271879|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/iuvbio/pandas_ods_reader^0|1T|6|2Q|8|1I|7|0|0|5|T|0^^$0|@$1|2|3|4|5|6|7|P|8|@$9|Q|A|R|B|C]|$9|S|A|T|B|C]]|D|@$9|U|A|V|1|W]]|E|$]]|$1|F|3|G|5|6|7|X|8|@$9|Y|A|Z|B|C]]|D|@]|E|$]]|$1|H|3|-4|5|6|7|10|8|@]|D|@]|E|$]]]|I|$J|$5|K|L|M|E|$N|O]]]]

Based heavily on the answer by davidovitch (thank you), I have put together a <a href="https://github.com/iuvbio/pandas_ods_reader" rel="nofollow noreferrer">package</a> that reads in a .ods file and returns a DataFrame. It's not a full implementation in <code>pandas</code> itself, such as his PR, but it provides a simple <code>read_ods</code> function that does the job.

You can install it with <code>pip install pandas_ods_reader</code>. It's also possible to specify whether the file contains a header row or not, and to specify custom column names.

blocks|key|55471|text|一些回应指出，需要odfpy或其他外部包才能获得此功能，但请注意，在最近的Pandas版本中(当前是1.1，8-2020)，在pd.ExcelWriter()和pd.read_excel()等函数中支持ODS格式。您只需指定支持引擎"odf“即可处理OpenDocument文件格式(.odf、.ods、.odt)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|55472|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

Some responses have pointed out that odfpy or other external packages are needed to get this functionality, but note that in recent versions of Pandas (current is 1.1, August-2020) there is support for ODS format in functions like pd.ExcelWriter() and pd.read_excel(). You only need to specify the propper engine &quot;odf&quot; to be able of working with OpenDocument file formats (.odf, .ods, .odt).

blocks|key|55524|text|pandas现在支持.ods文件。您必须先安装odfpy模块。然后它就会像一个普通的.xls文件一样工作。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|55525|conda+install+-c+conda-forge+odfpyr|code-block|syntax|javascript|55526|然后|55527|pd.read_excel('FILE_NAME.ods',+engine='odf')|55528|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

pandas now supports .ods files. you must install the odfpy module first. then it will work like a normal .xls file.
 
<pre><code>conda install -c conda-forge odfpyr
</code></pre>
then
 
<pre><code>pd.read_excel('FILE_NAME.ods', engine='odf')
</code></pre>

The Python library <a href="/questions/tagged/pandas" class="post-tag" title="show questions tagged &#39;pandas&#39;" rel="tag">pandas</a> can read Excel spreadsheets and convert them to a <code>pandas.DataFrame</code> with <code>pandas.read_excel(file)</code> command. Under the hood, it uses <a href="https://pypi.python.org/pypi/xlrd" rel="noreferrer">xlrd</a> library which <a href="https://github.com/python-excel/xlrd/blob/fcfdb721abe650c0b25d8a874dc7314e9eb8dc59/xlrd/__init__.py#L146" rel="noreferrer">does not support</a> ods files.

Is there an equivalent of <code>pandas.read_excel</code> for ods files? If not, how can I do the same for an Open Document Formatted spreadsheet (ods file)? ODF is used by LibreOffice and OpenOffice.

How to convert OpenDocument spreadsheets to a pandas DataFrame?

Python

Linux

Python库可以读取Excel电子表格，并使用pandas.read_excel(file)命令将其转换为pandas.DataFrame。在引擎盖下，它使用了库，该库用于 ods文件。是否有用于ods文件的等价物pandas.read_excel？如果没有，我如何对Open Document格式的电子表格(ods文...

问如何将OpenDocument电子表格转换为pandas DataFrame？
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