DataFrame合并：合并重叠数据combine_first

from pandas import DataFrame,Series
import numpy as np

a = Series([np.nan,2.5,np.nan,3.5,4.5,np.nan],
           index=['f','e','d','c','b','a'])
print(a)
'''
f    NaN
e    2.5
d    NaN
c    3.5
b    4.5
a    NaN
dtype: float64
'''
b = Series(np.arange(len(a),dtype=np.float64),
           index=['f','e','d','c','b','a'])
print(b)
'''
f    0.0
e    1.0
d    2.0
c    3.0
b    4.0
a    5.0
dtype: float64
'''
print(b[:-2])
'''
f    0.0
e    1.0
d    2.0
c    3.0
dtype: float64
'''
print(a[2:])
'''
d    NaN
c    3.5
b    4.5
a    NaN
dtype: float64
'''
# 索引全部或部分重叠的两个数据集
# combine_first 用参数对象的数据未调用者对象的缺失数据“打补丁”
print(b[:-2].combine_first(a[2:]))
'''
a    NaN
b    4.5
c    3.0
d    2.0
e    1.0
f    0.0
dtype: float64
'''

df1 = DataFrame({'a':[1.0,np.nan,5.0,np.nan],
                 'b':[np.nan,2.0,np.nan,6.0],
                 'c': range(2,18,4)})
print(df1)
'''
     a    b   c
0  1.0  NaN   2
1  NaN  2.0   6
2  5.0  NaN  10
3  NaN  6.0  14
'''
df2 = DataFrame({'a':[5.0,4.0,np.nan,3.0,7.0],
                 'b':[np.nan,3,4,6,8]})
print(df2)
'''
     a    b
0  5.0  NaN
1  4.0  3.0
2  NaN  4.0
3  3.0  6.0
4  7.0  8.0
'''
print(df1.combine_first(df2))
'''
     a    b     c
0  1.0  NaN   2.0
1  4.0  2.0   6.0
2  5.0  4.0  10.0
3  3.0  6.0  14.0
4  7.0  8.0   NaN
'''