如何在 pandas 中用空列表[]填充数据框Nan值? [英] How to fill dataframe Nan values with empty list [] in pandas?
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问题描述
这是我的数据框:
date ids
0 2011-04-23 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...
1 2011-04-24 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...
2 2011-04-25 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...
3 2011-04-26 Nan
4 2011-04-27 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...
5 2011-04-28 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...
我想用[]替换Nan
.怎么做? Fillna([])无效.我什至尝试了replace(np.nan, [])
,但它给出了错误:
I want to replace Nan
with []. How to do that? Fillna([]) did not work. I even tried replace(np.nan, [])
but it gives error:
TypeError('Invalid "to_replace" type: \'float\'',)
推荐答案
您可以首先使用loc
在ids
列中找到所有具有nan
的行,然后使用
You can first use loc
to locate all rows that have a nan
in the ids
column, and then loop through these rows using at
to set their values to an empty list:
for row in df.loc[df.ids.isnull(), 'ids'].index:
df.at[row, 'ids'] = []
>>> df
date ids
0 2011-04-23 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
1 2011-04-24 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
2 2011-04-25 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
3 2011-04-26 []
4 2011-04-27 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
5 2011-04-28 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
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