Python 我怎样才能同时提取和填充?
假设我有三个数据帧:Python 我怎样才能同时提取和填充?,python,pandas,Python,Pandas,假设我有三个数据帧: from pandas import DataFrame df1 = DataFrame([ [1], [3], [4] ], index=[1, 3, 4], columns=['value1'] ) df2 = DataFrame([ [5], [6], [7], ], index=[5, 6, 7], columns=['value2'] ) df3 = DataFrame([
from pandas import DataFrame
df1 = DataFrame([
[1],
[3],
[4]
],
index=[1, 3, 4],
columns=['value1']
)
df2 = DataFrame([
[5],
[6],
[7],
],
index=[5, 6, 7],
columns=['value2']
)
df3 = DataFrame([
[5, 9],
[6, 10],
[7, 11],
[8, 12]
],
index=[5, 6, 7, 8],
columns=['value1', 'value2']
)
使用
现在给我
value1 value2 value1 value2
1 1.0 NaN NaN NaN
3 3.0 NaN NaN NaN
4 4.0 NaN NaN NaN
5 NaN 5.0 5.0 9.0
6 NaN 6.0 6.0 10.0
7 NaN 7.0 7.0 11.0
8 NaN NaN 8.0 12.0
现在,我怎样才能得到结果呢
value1 value2
1 1.0 NaN
3 3.0 NaN
4 4.0 NaN
5 5.0 5.0
6 5.0 6.0
7 7.0 7.0
8 8.0 12.0
换句话说,对于相同名称的列,如何“向左”合并它们?我正在寻找一种通用解决方案,它可以接受任意数量的同名多列(也可以具有只出现一次的列名)。使用:
使用数据帧列表
更通用的解决方案是:
伟大的必须添加
DataFrame()
作为初始值(减少的第三个参数)。
value1 value2
1 1.0 NaN
3 3.0 NaN
4 4.0 NaN
5 5.0 5.0
6 5.0 6.0
7 7.0 7.0
8 8.0 12.0
df = df1.combine_first(df2).combine_first(df3)
print (df)
value1 value2
1 1.0 NaN
3 3.0 NaN
4 4.0 NaN
5 5.0 5.0
6 6.0 6.0
7 7.0 7.0
8 8.0 12.0
from functools import reduce
dfs = [df1, df2, df3]
df = reduce(lambda l,r: pd.DataFrame.combine_first(l,r), dfs)