Python version: Python 2.7.13 :: Anaconda custom (64-bit) Pandas version: pandas 0.20.2
Python版本：Python 2.7.13 :: Anaconda自定义（64位）Pandas版本：pandas 0.20.2
Hello,
你好，
I have a quite simple requirement. I would like to read an excel file and write a specific sheet to a csv file. Blank values in the source Excel file should be treated / written as blank when writing the csv file. However, my blank records are always written as 'nan' to the output file. (without the quotes)
我有一个非常简单的要求。我想阅读一个excel文件并将特定表格写入csv文件。编写csv文件时，源Excel文件中的空白值应被视为空白。但是，我的空白记录始终写为输出文件的“nan”。 （没有报价）
I read the Excel file via method
我通过方法读取Excel文件
read_excel(xlsx, sheetname='sheet1', dtype = str)
read_excel（xlsx，sheetname ='sheet1'，dtype = str）
I am specifying dtype because I have some columns that are numbers but should be treated as string. (Otherwise they might lose leading 0s etc) i.e. I would like to read the exact value from every cell.
我指定dtype因为我有一些数字列但应该被视为字符串。 （否则他们可能会丢失前导0等），即我想从每个单元格中读取确切的值。
Now I write the output .csv file via to_csv(output_file,index=False,mode='wb',sep=',',encoding='utf-8')
现在我通过to_csv写出输出.csv文件（output_file，index = False，mode ='wb'，sep ='，'，encoding ='utf-8'）
However, my result csv file contains nan for all blank cells from the excel file.
但是，我的结果csv文件包含来自excel文件的所有空白单元格的nan。
What am I missing? I already tried .fillna('', inplace=True) function but it seems to be doing nothing to my data. I also tried to add parameter na_rep ='' to the to_csv method but without success.
我错过了什么？我已经尝试过.fillna（''，inplace = True）函数，但它似乎对我的数据没有任何作用。我还尝试将参数na_rep =''添加到to_csv方法但没有成功。
Thanks for any help!
谢谢你的帮助！
Addendum: Please find hereafter a reproducible example.
附录：请在下文中找到可重复的示例。
Please find hereafter a reproducible example code. Please first create a new Excel file with 2 columns with the following content: COLUMNA COLUMNB COLUMNC 01 test 02 test
03 test
请在下文中找到可重现的示例代码。请首先使用以下内容创建一个包含2列的新Excel文件：COLUMNA COLUMNB COLUMNC 01 test 02 test 03 test
(I saved this Excel file to c:\test.xls Please note that 1st and 3rd row for column B as well as the 2nd row for Column C is blank/empty)
（我将此Excel文件保存到c：\ test.xls请注意，列B的第1行和第3行以及列C的第2行为空/空）
Now here is my code:
现在这是我的代码：
import pandas as pd
xlsx = pd.ExcelFile('c:\\test.xlsx')
df = pd.read_excel(xlsx, sheetname='Sheet1', dtype = str)
df.fillna('', inplace=True)
df.to_csv('c:\\test.csv', index=False,mode='wb',sep=',',encoding='utf-8', na_rep ='')
My result is:
COLUMNA,COLUMNB,COLUMNC
01,nan,test
02,test,nan
03,nan,test
我的结果是：COLUMNA，COLUMNB，COLUMNC 01，nan，test 02，test，nan 03，nan，test
My desired result would be:
COLUMNA,COLUMNB,COLUMNC
01,,test
02,test,
03,,test
我想要的结果是：COLUMNA，COLUMNB，COLUMNC 01 ,, test 02，test，03 ,, test
1 个解决方案
#1
3
Since you are dealing with nan strings, you can the df.replace function:
由于你正在处理nan字符串，你可以使用df.replace函数：
In [625]: df = pd.DataFrame({'Col1' : ['nan', 'foo', 'bar', 'baz', 'nan', 'test']})
In [626]: df.replace('nan', '')
Out[626]:
Col1
0
1 foo
2 bar
3 baz
4
5 test
You can then write it to your file:
然后，您可以将其写入您的文件：
df.to_csv(output_file, index=False, mode='wb', sep=',', encoding='utf-8')
All 'nan' string values will be replaced by the empty string ''.
所有'nan'字符串值都将被空字符串''替换。
#1
3
Since you are dealing with nan strings, you can the df.replace function:
由于你正在处理nan字符串，你可以使用df.replace函数：
In [625]: df = pd.DataFrame({'Col1' : ['nan', 'foo', 'bar', 'baz', 'nan', 'test']})
In [626]: df.replace('nan', '')
Out[626]:
Col1
0
1 foo
2 bar
3 baz
4
5 test
You can then write it to your file:
然后，您可以将其写入您的文件：
df.to_csv(output_file, index=False, mode='wb', sep=',', encoding='utf-8')
All 'nan' string values will be replaced by the empty string ''.
所有'nan'字符串值都将被空字符串''替换。