Scenаriо. A functiоn reаds vаlues frоm data.csv, skips invalid numeric entries, and returns summary information in a dictionary.ClipRun setup block: paste this first to create the file. import csv rows = [ ["A", "10"], ["B", "20"], ["C", "abc"], ["D", "30"] ] with open("data.csv", "w", newline="") as file: writer = csv.writer(file) writer.writerows(rows) This setup block creates the CSV file you will read in your solution. Task:1. Run the setup block once to create data.csv.2. Complete the student skeleton below for analyze_data(filename).3. Import the csv module.4. Open the file and use csv.reader() to read each row.5. Try to convert the second value in each row to a float; skip invalid values.6. Return a dictionary with keys "count", "total", and "average" (average rounded to 2 decimal places).7. Do not use input() or print() inside the function. Student skeleton: import csv def analyze_data(filename): values = [] result = {} with open(filename, "r") as file: reader = csv.reader(file) for row in reader: # row[0] is the label # row[1] is the value # convert row[1] to float # if the conversion fails, skip that line # store count, total, and average in result return result Example. then analyze_data("data.csv") returns:{"count": 3, "total": 60.0, "average": 20.0}