获取pandas.read_csv以将空值读取为空字符串而不是nan [英] Get pandas.read_csv to read empty values as empty string instead of nan

问题描述

我正在使用pandas库读取一些CSV数据.在我的数据中，某些列包含字符串.字符串"nan"是可能的值，空字符串也是.我设法让大熊猫将"nan"读取为字符串，但我不知道如何获取不读取空值作为NaN的方法.这是示例数据和输出

I'm using the pandas library to read in some CSV data. In my data, certain columns contain strings. The string "nan" is a possible value, as is an empty string. I managed to get pandas to read "nan" as a string, but I can't figure out how to get it not to read an empty value as NaN. Here's sample data and output

One,Two,Three
a,1,one
b,2,two
,3,three
d,4,nan
e,5,five
nan,6,
g,7,seven

>>> pandas.read_csv('test.csv', na_values={'One': [], "Three": []})
    One  Two  Three
0    a    1    one
1    b    2    two
2  NaN    3  three
3    d    4    nan
4    e    5   five
5  nan    6    NaN
6    g    7  seven

它正确地将"nan"读取为字符串"nan"，但仍将空单元格读取为NaN.我尝试将converters参数中的str传递给read_csv(使用converters={'One': str}))，但是它仍然将空单元格读取为NaN.

It correctly reads "nan" as the string "nan', but still reads the empty cells as NaN. I tried passing in str in the converters argument to read_csv (with converters={'One': str})), but it still reads the empty cells as NaN.

我意识到我可以用fillna填充读取后的值，但是真的没有办法告诉熊猫特定CSV列中的空单元格应读取为空字符串而不是NaN吗?

I realize I can fill the values after reading, with fillna, but is there really no way to tell pandas that an empty cell in a particular CSV column should be read as an empty string instead of NaN?

推荐答案

我添加了一个票证，以便在此处添加某种选项:

I added a ticket to add an option of some sort here:

https://github.com/pydata/pandas/issues/1450

与此同时，result.fillna('')应该做你想做的事

In the meantime, result.fillna('') should do what you want

在开发版本(最终为0.8.0)中，如果您指定na_values的空列表，则空字符串将在结果中保留空字符串

in the development version (to be 0.8.0 final) if you specify an empty list of na_values, empty strings will stay empty strings in the result

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