How to split pandas column containing several .json arrays?

IIUC this is exactly what json_normalize is for:

import pandas as pd

data = {"_id": {
    "$oid": "6090ba8fccd167ce183b5ebc"
  },
  "day": "2021-05-04",
  "sensorType": "eurecam",
  "sensorid": "74",
  "first": {
    "$numberLong": "1620097683000"
  },
  "last": {
    "$numberLong": "1620103653000"
  },
  "nsamples": 200,
  "samples": [
    {
      "occupancy_state": "1,0,0,0",
      "rtc_utc_time": "2021-05-04 03:07:58",
      "sdcard_site": "BE",
      "sdcard_chain": "DAG",
      "sdcard_line": "1,BE",
      "utc": {
        "$numberLong": "1620097683000"
      }
    },
    {
      "occupancy_state": "1,0,0,0",
      "rtc_utc_time": "2021-05-04 03:08:27",
      "sdcard_site": "BE",
      "sdcard_chain": "DAG",
      "sdcard_line": "1,BE",
      "utc": {
        "$numberLong": "1620097712000"
      }
    },
    {
      "occupancy_state": "1,0,0,0",
      "rtc_utc_time": "2021-05-04 03:08:57",
      "sdcard_site": "BE",
      "sdcard_chain": "DAG",
      "sdcard_line": "1,BE",
      "utc": {
        "$numberLong": "1620097742000"
      }
    }
  ]
}

df = pd.json_normalize(data, record_path="samples")
print(df)

Output:

  occupancy_state         rtc_utc_time sdcard_site sdcard_chain sdcard_line utc.$numberLong
0         1,0,0,0  2021-05-04 03:07:58          BE          DAG        1,BE   1620097683000
1         1,0,0,0  2021-05-04 03:08:27          BE          DAG        1,BE   1620097712000
2         1,0,0,0  2021-05-04 03:08:57          BE          DAG        1,BE   1620097742000