在 Pandas 中用 NaN 替换空字符串
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replacing empty strings with NaN in Pandas
提问by doctorer
I have a pandas dataframe (that was created by importing a csv file). I want to replace blank values with NaN. Some of these blank values are empty and some contain a (variable number) of spaces '', ' ', ' ', etc.
我有一个 Pandas 数据框（它是通过导入一个 csv 文件创建的）。我想用 NaN 替换空白值。一些这些空白值的是空的，一些包含一个（变量数）的空间''，' '，' '等。
Using the suggestion from this threadI have
使用这个线程的建议我有
df.replace(r'\s+', np.nan, regex=True, inplace = True)
which does replace all the strings that only contain spaces, but also replaces every string that has a space in it, which is not what I want.
它确实替换了所有只包含空格的字符串，但也替换了每个包含空格的字符串，这不是我想要的。
How do I replace only strings with justspaces and empty strings?
如何仅用空格和空字符串替换字符串？
采纳答案by Rajshekar Reddy
If you are reading a csvfile and want to convert all empty strings to nanwhile reading the fileitself then you can use the option
如果您正在读取csv文件并希望nan在读取文件本身时将所有空字符串转换为，那么您可以使用该选项
skipinitialspace=True
Example code
示例代码
pd.read_csv('Sample.csv', skipinitialspace=True)
This will remove any white spaces that appear after the delimiters, Thus making all the empty strings as nan
这将删除出现在分隔符之后的任何空格，从而使所有空字符串成为 nan
From the documentation http://pandas.pydata.org/pandas-docs/stable/io.html
从文档http://pandas.pydata.org/pandas-docs/stable/io.html
Note:This option will remove preceding white spaces even from valid data, if for any reason you want to retain the preceding white space then this option is not a good choice.
注意：此选项甚至会从有效数据中删除前面的空格，如果出于任何原因您想保留前面的空格，则此选项不是一个好的选择。
回答by Boud
Indicate it has to start with blank and end with blanks with ^ and $ :
表示它必须以空格开头并以空格结尾 ^ 和 $ ：
df.replace(r'^\s*$', np.nan, regex=True, inplace = True)
