Pandas select 基于列值的 DataFrame 行?

Pandas select rows from a DataFrame based on column values?

我已将以下 json 字符串加载到 dataframe。现在我想根据 ossId.

过滤记录

我的条件是给出错误信息。按ossId过滤的正确方法是什么?

import pandas as pd

data = """
{
  "components": [
    {
      "ossId": 3946,
      "project": "OALX",
      "licenses": [
        {
          "name": "BSD 3",
          "status": "APPROVED"
        }
      ]
    },
    {
      "ossId": 3946,
      "project": "OALX",
      "version": "OALX.client.ALL",
      "licenses": [
        {
          "name": "GNU Lesser General Public License v2.1 or later",
          "status": "APPROVED"
        }
      ]
    },
    {
      "ossId": 2550,
      "project": "OALX",
      "version": "OALX.webservice.ALL" ,
      "licenses": [
        {
          "name": "MIT License",
          "status": "APPROVED"
        }
      ]
    }
  ]
}
"""

df = pd.read_json(data)
print(df)

df1 = df[df["components"]["ossId"] == 2550]

您需要进入单元格的数据并获取正确的密钥:

df[df['components'].apply(lambda x: x.get('ossId')==2550)]

使用str

df[df.components.str['ossId']==2550]
Out[89]: 
                                          components
2  {'ossId': 2550, 'project': 'OALX', 'version': ...

我认为您的问题是由 json 结构引起的。您实际上是在 df 中加载了整个字段列表 component.

的一行

您应该改为将记录列表传递给数据框。类似于:

json_data = json.loads(data)
df = pd.DataFrame(json_data["components"])

filtered_data = df[df["ossId"] == 2550]