entityMap|blocks|key|557o2|text|您可以尝试遍历每个包含.xlxs的文件的目录，只需将YOUR_DIR替换为包含这些文件的文件夹的路径即可。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2gjf9|我已经添加了"+filename“，它只是一个没有扩展名的文件名，所以你可以将它添加到.csv文件名中|1pbo|import+os

directory+=+"\\YOUR_DIR\\HERE"
files+=+os.listdir(directory)

for+xlxs_file+in+files:
++++if+".xlxs"+in+xlxs_file:

++++++++filename+=+xlxs_file.strip(".xlxs")
++++++++xlxs_file+=+directory+%2B+"\\"+%2B+xlxs_file

++++++++data+=+pd.read_excel(xlxs_file,+sheet_name=None)
++++++++for+sheet_name,+df+in+data.items():
++++++++++++df.to_csv(f'{filename}_{sheet_name}.csv')|code-block|syntax|javascript|fgrkv^0|0|0|0^^$0|$]|1|@$2|3|4|5|6|7|8|K|9|@]|A|@]|B|$]]|$2|C|4|D|6|7|8|L|9|@]|A|@]|B|$]]|$2|E|4|F|6|G|8|M|9|@]|A|@]|B|$H|I]]|$2|J|4|-4|6|7|8|N|9|@]|A|@]|B|$]]]]

You could try looping through the directory for each file that has .xlxs, just replace YOUR_DIR with your own path to folder containing the files.
I've added &quot;filename&quot; which is just filename without extension so you can add this to .csv filename
<pre><code>import os

directory = &quot;\\YOUR_DIR\\HERE&quot;
files = os.listdir(directory)

for xlxs_file in files:
 if &quot;.xlxs&quot; in xlxs_file:

 filename = xlxs_file.strip(&quot;.xlxs&quot;)
 xlxs_file = directory + &quot;\\&quot; + xlxs_file

 data = pd.read_excel(xlxs_file, sheet_name=None)
 for sheet_name, df in data.items():
 df.to_csv(f'{filename}_{sheet_name}.csv')
</code></pre>

entityMap|blocks|key|9pd7o|text|只要每个文件中的sheetnames是相同的，那么这应该是可行的：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|rhhl|import+os
import+pandas+as+pd

#+target+directory+where+the+workbooks+lie
tgt_dir+=+r'paste\directory\here\make\sure\to\keep\letter\r\before\quote'

#+list+of+any+files+within+the+dir+that+have+.xlsx+in+them
list_xl_files+=+[f+for+f+in+os.listdir(tgt_dir)+if+'.xlsx'+in+f.lower()]

#+type+a+list+of+the+sheets+you+want+to+target+and+extract
list_target_sheets+=+['Sheet1',+'Sheet2',+'etc']

#+iterate+through+each+file+and+for+each+sheet+in+target+sheets
for+xl_file+in+list_xl_files:
++++for+sheet+in+list_target_sheets:
++++++++
++++++++#+read+in+the+file+and+target+sheet
++++++++df+=+pd.read_excel(tgt_dir%2B'\\'%2Bxl_file,+sheet_name=sheet)
++++++++
++++++++#+export+to+csv+but+replace+.xlsx+with+nothing+
++++++++#+then+add+_sheetname.csv+so+the+filename+shows+the+sheet+too
++++++++df.to_csv(tgt_dir%2B'\\'%2Bxl_file.replace('.xlsx','')%2B'_'%2Bsheet_name%2B'.csv')|code-block|syntax|javascript|9giaa^0|0|0^^$0|$]|1|@$2|3|4|5|6|7|8|I|9|@]|A|@]|B|$]]|$2|C|4|D|6|E|8|J|9|@]|A|@]|B|$F|G]]|$2|H|4|-4|6|7|8|K|9|@]|A|@]|B|$]]]]

So long as the sheetnames are the same in each file then this should work:
<pre><code>import os
import pandas as pd

# target directory where the workbooks lie
tgt_dir = r'paste\directory\here\make\sure\to\keep\letter\r\before\quote'

# list of any files within the dir that have .xlsx in them
list_xl_files = [f for f in os.listdir(tgt_dir) if '.xlsx' in f.lower()]

# type a list of the sheets you want to target and extract
list_target_sheets = ['Sheet1', 'Sheet2', 'etc']

# iterate through each file and for each sheet in target sheets
for xl_file in list_xl_files:
 for sheet in list_target_sheets:
 
 # read in the file and target sheet
 df = pd.read_excel(tgt_dir+'\\'+xl_file, sheet_name=sheet)
 
 # export to csv but replace .xlsx with nothing 
 # then add _sheetname.csv so the filename shows the sheet too
 df.to_csv(tgt_dir+'\\'+xl_file.replace('.xlsx','')+'_'+sheet_name+'.csv')
</code></pre>

entityMap|blocks|key|88ebj|text|不幸的是，有些文件有额外的传感器和数据，这意味着额外的工作表。但我现在让这段代码正常工作了：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|566cc|import+os
import+pandas+as+pd

directory+=+"./"
files+=+os.listdir(directory)
for+xlxs_file+in+files:
++++if+".xlsx"+in+xlxs_file:
++++++++filename+=+xlxs_file.strip(".xlsx")
++++++++xlxs_file+=+os.path.join(directory,+xlxs_file)
++++++++data+=+pd.read_excel(xlxs_file,+sheet_name=None)
++++++++for+sheet_name,+df+in+data.items():
++++++++++++df.to_csv("{}-{}.csv".format(filename,+sheet_name))|code-block|syntax|javascript|3enph^0|0|0^^$0|$]|1|@$2|3|4|5|6|7|8|I|9|@]|A|@]|B|$]]|$2|C|4|D|6|E|8|J|9|@]|A|@]|B|$F|G]]|$2|H|4|-4|6|7|8|K|9|@]|A|@]|B|$]]]]

Some files unfortunatly have extra sensors &amp; data which means extra workssheets. But i got this code working now:
<pre><code>import os
import pandas as pd

directory = &quot;./&quot;
files = os.listdir(directory)
for xlxs_file in files:
 if &quot;.xlsx&quot; in xlxs_file:
 filename = xlxs_file.strip(&quot;.xlsx&quot;)
 xlxs_file = os.path.join(directory, xlxs_file)
 data = pd.read_excel(xlxs_file, sheet_name=None)
 for sheet_name, df in data.items():
 df.to_csv(&quot;{}-{}.csv&quot;.format(filename, sheet_name))
</code></pre>

For the purpose of writing my thesis mechanical engineering i recieved a lot of sensor data that is configured in multiple excel files(100) with multiple sheets(22).
Now i want to visualize this into power Bi but the .xlxs files a working way to slow so i want all the data(sheets) in seperate CSV files.
I dont have any real experience with programming but will be able to run a script in jupyter or spyder.
I tried a code in VBA that configured multiple excels into csv, but this only worked for the first sheet in the .xlsx file.
I also used the code below in jupyter notebook; but this gives me all the sheets for one single excel.
<pre><code>data = pd.read_excel('file_name.file_format', sheet_name=None)

for sheet_name, df in data.items():
 df.to_csv(f'{sheet_name}.csv')
</code></pre>
Does someone has a code for this purpose or does someone know how to adjust the code above to do this with all excel files in a folder?

Extracting CSV files from multiple .xlxs files with multiple worksheets [answered]

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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 为了写我的论文机械工程，我收到了许多传感器数据，这些数据配置在多个excel文件(100)和多张表(22)中。现在我想把它可视化到power Bi中，但是.xlxs文件的速度很慢，所以我想把所有的数据(工作表)放在单独的CSV文件中。我没有任何真正的编程经验，但将能够在jupyter或spyder运行脚本。 我尝试了...

问从具有多个工作表的多个.xlxs文件中提取CSV文件[已回答]
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问从具有多个工作表的多个.xlxs文件中提取CSV文件[已回答]EN