measure the time interval for each ECU (identified by the arbitration ID).

function ecu_time_interval(arbitration_id, data) that returns the list that contains the time interval between each data point for the chosen arbitration ID in the dataset.

Ensure to convert data types as appropriate. Since the columns may vary between datasets, the index of the timestamp column must be checked.

As we are calculating the time differences, the size of the returning list will be one less than the size of the data for the chosen arbitration_ID.

the following code may help your answer:

def get_data(filename):
  # Open the file in read mode
  with open(filename, 'r') as file:
      # Read all lines from the file
      lines = file.readlines()
     
      # Initialize an empty list to store the data
      data = []
     
      # Iterate over the lines, splitting each line by comma and appending the result to the data list
      for line in lines:
          entry = line.strip().split(',')
          data.append(entry)
     
      # Return the resulting nested list
      return data

 

def unique_id(data):
   # Identify the column index for the 'ID' header
   header = data[0]
   id_col_index = header.index('Arbitration_ID')
   
   # Extract the IDs from the data and convert them to a set to remove duplicates
   ids = set(row[id_col_index] for row in data[1:])
   
   # Sort the IDs in ascending order and return as a list
   return sorted(ids)

def ecu_data(arbitration_id, data):
   # Find the index of the column with the given arbitration ID
   header = data[0]
   id_col_index = header.index('Arbitration_ID')
   
   # Collect the rows that match the given arbitration ID
   matching_rows = [row for row in data[1:] if row[id_col_index] == arbitration_id]
   
   
   # Return the resulting nested list
   return matching_rows