Compute window averages and merge intervals

You are given two independent pandas tasks.

1. Sliding-window average
   • Input DataFrame: df
   • Schema:
     • row_id INT — unique row order key, already sorted ascending
     • value FLOAT
   • Given an integer k >= 0 , compute for each row the average of the values from the previous k rows, the current row, and the next k rows.
   • If a row does not have at least k previous rows and k next rows, set the output to -1 for that row.
   • Return a DataFrame with columns: row_id , value , window_avg .
2. Merge overlapping autonomous-driving intervals
   • Input DataFrame: segments
   • Schema:
     • vehicle_id STRING
     • event_type STRING
     • start_ts TIMESTAMP
     • end_ts TIMESTAMP
   • Assume all timestamps are in the same timezone and start_ts <= end_ts for every row.
   • For each (vehicle_id, event_type) independently, merge intervals that overlap or touch, where a new interval should be merged into the current one if next.start_ts <= current.end_ts .
   • Return the merged result with columns: vehicle_id , event_type , merged_start_ts , merged_end_ts , sorted by vehicle_id , event_type , merged_start_ts .

Write pandas code for both tasks.