> For the complete documentation index, see [llms.txt](https://jen-hsuan-hsieh.gitbook.io/python/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://jen-hsuan-hsieh.gitbook.io/python/chapter-2courses/21python-for-data-science-and-machine-learning-bootcamp/214python-for-data-analysis-pandas/2146merging-joining-and-concatenating.md).

# 2.1.4.6.Merging joining and Concatenating

## Concatenation

* 注意: Dataframe的維度必須相同

```
pd.concate([df1, df2, df3])

pd.concate([df1, df2, df3], axis = 1)
```

## Merge

* 只能做**橫向合併**
* 預設的merge的方式為[inner](https://jenhsuan.gitbooks.io/database/content/chapter1/12mysql-for-beginners/125using-joins-to-combine-tables/1251inner-join.html)
  * [Inner join: 找出table間有共同key值的資料](https://jenhsuan.gitbooks.io/database/content/chapter1/12mysql-for-beginners/125using-joins-to-combine-tables/1251inner-join.html)

    ```
    pd.merge(left, right, how = 'inner', on = 'key')
    ```
  * 指定多個key進行inner join

    ```
    pd.merge(left, right, on = ['key1', 'key2'])
    ```
  * [right join: 以right的key為主, 加入left](https://jenhsuan.gitbooks.io/database/content/chapter1/12mysql-for-beginners/125using-joins-to-combine-tables/1253right-join.html)

    ```
    pd.merge(left, right, how = 'right', on = ['key1', 'key2'])
    ```
  * [left join: 以left的key為主, 加入right](https://jenhsuan.gitbooks.io/database/content/chapter1/12mysql-for-beginners/125using-joins-to-combine-tables/1252left-join.html)

    ```
    pd.merge(left, right, how = 'left', on = ['key1', 'key2'])
    ```
  * [outer join: left與right的left join table跟left與right的right join table 做union](https://jenhsuan.gitbooks.io/database/content/chapter1/12mysql-for-beginners/125using-joins-to-combine-tables/1254full-join.html)

    ```
    pd.merge(left, right, how = 'outer', on = ['key1', 'key2'])
    ```
* 如果除了key以外有其他的column也是同名的, 將會採用\[列名\_表名]作為新的column值

```
left = pd.DataFrame({'key': ['K0', 'K1', 'K2', 'K3'],
                     'C': ['A0', 'A1', 'A2', 'A3'],
                     'D': ['B0', 'B1', 'B2', 'B3']})

right = pd.DataFrame({'key': ['K0', 'K1', 'K2', 'K3'],
                          'C': ['C0', 'C1', 'C2', 'C3'],
                          'D': ['D0', 'D1', 'D2', 'D3']}) 

pd.merge(left,right,how='inner',on='key')
OUT:     
       C_x    D_x    key    C_y    D_y
0    A0    B0    K0    C0    D0
1    A1    B1    K1    C1    D1
2    A2    B2    K2    C2    D2
3    A3    B3    K3    C3    D3
```

## Join

* 可以做**橫向或縱向合併**

```
left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
                     'B': ['B0', 'B1', 'B2']},
                      index=['K0', 'K1', 'K2']) 

right = pd.DataFrame({'C': ['C0', 'C2', 'C3'],
                    'D': ['D0', 'D2', 'D3']},
                      index=['K0', 'K2', 'K3'])

left.join(right, how='outer')
```