我是pyspark和pandas的新用户。我们有包含datetime，timeid，edgeId和speed（y）的道路网络数据。下面给出的数据集包含每个edgeId的4周的15分钟频率星期一数据。每个edgeId和时间的下一个星期一速度是什么。
输入

+-------------------+------+--------+----+
|                 ds|timeId|  edgeId|   y|
+-------------------+------+--------+----+
|2022-11-07 00:00:00|     1|73215790|34.0|
|2022-11-21 00:00:00|     1|73215790|50.0|
|2022-11-28 00:00:00|     1|73215790|50.0|
|2022-12-05 00:00:00|     1|73215790|50.0|
|2022-12-12 00:00:00|     1|73215790|50.0|
|2022-12-19 00:00:00|     1|73215790|50.0|
|2022-12-26 00:00:00|     1|73215790|41.0|
|2023-01-02 00:00:00|     1|73215790|44.0|
|2023-01-09 00:00:00|     1|73215790|46.0|
|2022-11-07 00:15:00|     2|73215790|50.0|
|2022-11-21 00:15:00|     2|73215790|50.0|
|2022-11-28 00:15:00|     2|73215790|42.6|
|2022-12-05 00:15:00|     2|73215790|50.0|
|2022-12-12 00:15:00|     2|73215790|50.0|
|2022-12-19 00:15:00|     2|73215790|50.0|
|2022-12-26 00:15:00|     2|73215790|41.1|
|2023-01-02 00:15:00|     2|73215790|44.0|
|2023-01-09 00:15:00|     2|73215790|46.0|

输出应为

+-------------------+------+--------+----+
|                 ds|timeId|  edgeId|   y|
+-------------------+------+--------+----+
|2023-01-16 00:00:00|     1|73215790|50.0|
|2023-01-16 00:15:00|     2|73215790|50.0|

请如何预测使用fbprophet或任何其他模块。