先创建两组数据a和b
In [
62]: a=pd
.Series([np
.nan,
2.5,np
.nan,
3.5,
4.5,np
.nan],index=[
'f',
'e',
'd',
'c',
'b',
'a'])
In [
63]: b=pd
.Series([
1,np
.nan,
3,
4,
5,np
.nan],index=[
'f',
'e',
'd',
'c',
'b',
'a'])
In [
64]: a
Out[
64]:
f NaN
e
2.5
d NaN
c
3.5
b
4.5
a NaN
dtype: float64
In [
65]: b
Out[
65]:
f
1.0
e NaN
d
3.0
c
4.0
b
5.0
a NaN
dtype: float64
用a的数据填补b的缺失值
In [
66]: b
.combine_first(a)
Out[
66]:
f
1.0
e
2.5
d
3.0
c
4.0
b
5.0
a NaN
dtype: float64
用b的数据填补a的缺失值
In [
67]: a
.combine_first(b)
Out[
67]:
f
1.0
e
2.5
d
3.0
c
3.5
b
4.5
a NaN
dtype: float64
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