What is the easiest way to merge two data frames with exclusive indexes?-CodePudding

Let's say you have two data frames:

import pandas as pd

df1 = pd.DataFrame(
    {
        "A": ["A0", "A1", "A3", "A5"],
        "B": ["B0", "B1", "B3", "B5"],
    },
    index=[0, 1, 3, 5],
)

print(df1)

df2 = pd.DataFrame(
    {
        "A": ["A2", "A4"],
        "B": ["B2", "B4"],
    },
    index=[2, 4],
)

print(df2)

How can I merge the two df1 and df2 frames in Python to obtain the following df3 data frame:

df3 = pd.DataFrame(
    {
        "A": ["A0", "A1", "A2", "A3", "A4", "A5"],
        "B": ["B0", "B1", "B2", "B3", "B4", "B5"],
    },
    index=[0, 1, 2, 3, 4, 5],
)

print(df3)

The goal is to combine the two data frames into one.

Thanks

I tried the concat() function but it's not working as I want the indexes to be sorted in ascending order [0 1 2 3 4 5].

frames = [df1, df2]

df3 = pd.concat(frames)

CodePudding user response：

Adding sort_index at the end

df3 = pd.concat(frames).sort_index()
df3
Out[85]: 
    A   B
0  A0  B0
1  A1  B1
2  A2  B2
3  A3  B3
4  A4  B4
5  A5  B5