在DataFrame索引中替换NaN
问题描述：
我有一个看起来像这样的DataFrame:
I have a DataFrame which looks like this:
one | two
a | 2 | 5
b | 3 | 6
NaN | 0 | 0
如何用一个字符串替换索引中的NaN，说无标签"?
How do I replace the NaN in the index with a string, say "No label"?
我尝试过:
df = df.replace(np.NaN, "No label")
和
df.index = df.index.replace(np.NaN, "No label")
但是得到了
TypeError: expected string or buffer
答
您可以先将原始索引作为系列处理，然后重新分配索引:
You can process the original index as a Series first and then re-assign the index:
import pandas as pd
import numpy as np
df = pd.DataFrame({'one': [2, 3, 0], 'two': [5, 6, 0]}, index=['a', 'b', np.nan])
df.index = pd.Series(df.index).replace(np.nan, 'No label')
print df
输出:
one two
a 2 5
b 3 6
No label 0 0