问题

我正在尝试将一个包含其他列信息的列添加到我的数据框中，格式为json对象

我的数据框如下所示：

| col_1| col_2|
|:---- |:------:|
| 1| 1|
|2|2|

然后，我尝试使用以下代码添加json列

```python
for i, row in df.iterrows():
    i_val = row.to_json()
    df.at[i, 'raw_json'] = i_val

然而，结果是一个"级联"数据框，其中json出现两次

我希望它看起来像以下这样

<details>
<summary>英文:</summary>

I&#39;m trying add a column to my dataframe that contains the information from the other columns as a json object

My dataframe looks like this:

| col_1| col_2|
|:---- |:------:|
| 1| 1|
|2|2|

I&#39;m then trying to add the json column using the following

```python
    for i, row in df:
        i_val = row.to_json()
        df.at[i,&#39;raw_json&#39;] = i_val

However it results in a "cascaded" dataframe where the json appears twice

I'm expecting it to look like the following

答案1

得分: 3

使用df.to_json(orient='records')

df['raw_json'] = df.to_json(orient='records')

col_1  col_2                                       raw_json
0      1      1  [{"col_1":1,"col_2":1},{"col_1":2,"col_2":2}]
1      2      2  [{"col_1":1,"col_2":1},{"col_1":2,"col_2":2}]

df['raw_json'] = df.to_json(orient='records')


   col_1  col_2                                       raw_json
0      1      1  [{"col_1":1,"col_2":1},{"col_1":2,"col_2":2}]
1      2      2  [{"col_1":1,"col_2":1},{"col_1":2,"col_2":2}]

答案2

得分: 0

使用列表推导和itterrows（如果您想要JSON，可以删除[0]中的字典部分）：

df["raw_json"] = [pd.DataFrame(data=[row], columns=df.columns).to_dict(orient="records")[0] for _, row in df.iterrows()]
print(df)

输出：

   col_1  col_2                  raw_json
0      1      1  {'col_1': 1, 'col_2': 1}
1      2      2  {'col_1': 2, 'col_2': 2}

df["raw_json"] = [pd.DataFrame(data=[row], columns=df.columns).to_dict(orient="records")[0] for _, row in df.iterrows()]
print(df)

   col_1  col_2                  raw_json
0      1      1  {'col_1': 1, 'col_2': 1}
1      2      2  {'col_1': 2, 'col_2': 2}