Pandas-通过对列和索引的值求和来合并两个数据框

Question

I want to merge two datasets by indexes and columns.

I want to merge entire dataset

df1 = pd.DataFrame([[1, 0, 0], [0, 2, 0], [0, 0, 3]],columns=[1, 2, 3])
df1
    1   2   3
0   1   0   0
1   0   2   0
2   0   0   3

df2 = pd.DataFrame([[0, 0, 1], [0, 2, 0], [3, 0, 0]],columns=[1, 2, 3])
df2
    1   2   3
0   0   0   1
1   0   2   0
2   3   0   0

I have tried this code but I got this error. I can't get why it shows the size of axis as an error.

df_sum = pd.concat([df1, df2])\
       .groupby(df2.index)[df2.columns]\
       .sum().reset_index()

ValueError: Grouper and axis must be same length

This was what I expected the output of df_sum

df_sum
    1   2   3
0   1   0   1
1   0   4   0
2   3   0   3

Answer 1

You can use : df1.add(df2, fill_value=0) . It will add df2 into df1 also it will replace NAN value with 0 .

>>> import numpy as np
>>> import pandas as pd
>>> df2 = pd.DataFrame([(10,9),(8,4),(7,np.nan)], columns=['a','b'])
>>> df1 = pd.DataFrame([(1,2),(3,4),(5,6)], columns=['a','b'])
>>> df1.add(df2, fill_value=0)

    a     b
0  11  11.0
1  11   8.0
2  12   6.0