Descriptive Statistics Calculator Write a Python function to calculate various descriptive statistics metrics for a given dataset. The function should take a list or NumPy array of numerical values and return a dictionary containing mean, median, mode, variance, standard deviation, percentiles (25th, 50th, 75th), and interquartile range (IQR). Example: Input: [10, 20, 30, 40, 50] Output: {'mean': 30.0, 'median': 30.0, 'mode': 10, 'variance': 200.0, 'standard_deviation': 14.142135623730951, '25th_percentile': 20.0, '50th_percentile': 30.0, '75th_percentile': 40.0, 'interquartile_range': 20.0} import numpy as np def descriptive_statistics(data): # Your code here stats_dict = { "mean": mean, "median": median, "mode": mode, "variance": np.round(variance,4), "standard_deviation": np.round(std_dev,4), "25th_percentile": percentiles[0], "50th_percentile": percentiles[1], "75th_percentile": percentiles[2], "interquartile_range": iqr } return {}