pandas Python Reindex 生成 Nan
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Python Reindex Producing Nan
提问by Adam Warner
Here is the code that I am working with:
这是我正在使用的代码：
import pandas as pd
import pandas as pd
test3 = pd.Series([1,2,3], index = ['a','b','c'])
test3 = test3.reindex(index = ['f','g','z'])
So originally every thing is fine and test3 has an index of 'a' 'b' 'c' and values 1,2,3. But then when I got to reindex test3 I get that my values 1 2 3 are lost. Why is that? The desired output would be:
所以最初一切都很好，test3 的索引为 'a' 'b' 'c' 并且值为 1,2,3。但是当我重新索引 test3 时，我发现我的值 1 2 3 丢失了。这是为什么？所需的输出是：
f 1
g 2
z 3
采纳答案by EdChum
The docsare clear on this behaviour :
该文档是对这种行为清楚：
Conform Series to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index
通过可选的填充逻辑使 Series 符合新索引，将 NA/NaN 放置在先前索引中没有值的位置
if you just want to overwrite the index values then do:
如果您只想覆盖索引值，请执行以下操作：
In [32]:
test3.index = ['f','g','z']
test3
Out[32]:
f 1
g 2
z 3
dtype: int64
