answer:def count_unique_words(input_string): # Convert the input string to lowercase and remove punctuation clean_string = ''.join(char for char in input_string.lower() if char.isalnum() or char == ' ') # Split the cleaned string into a list of words word_list = clean_string.split() # Create a set to store unique words unique_words = set(word_list) # Return the length of the set (count of unique words) return len(unique_words)

answer:Here's the Python function to find the year with the highest population growth rate compared to the previous year:```pythondef find_year_with_highest_growth_rate(population_data): max_growth_rate = 0 year_with_max_growth = None for i in range(1, len(population_data)): current_year = population_data[i]['year'] previous_year = population_data[i - 1]['year'] current_population = population_data[i]['population'] previous_population = population_data[i - 1]['population'] if previous_population != 0: growth_rate = (current_population - previous_population) / previous_population * 100 if growth_rate > max_growth_rate: max_growth_rate = growth_rate year_with_max_growth = current_year return year_with_max_growth```This function takes a list of dictionaries `population_data` as input, where each dictionary represents a year and its corresponding population. It iterates through the list, calculating the population growth rate for each year compared to the previous year. The function keeps track of the maximum growth rate and the corresponding year. Finally, it returns the year with the highest growth rate.Note that the function assumes that the list `population_data` is sorted in ascending order by year. If the previous population is zero, the growth rate is not calculated to avoid division by zero.

answer:Here's the Python function to find the study with the highest average number of patients:```pythondef find_study_with_highest_avg_patients(studies): highest_avg_study = None highest_avg = 0 for study in studies: study_name = study["study_name"] patients_per_month = study["patients_per_month"] avg_patients = sum(patients_per_month) / len(patients_per_month) if avg_patients > highest_avg: highest_avg = avg_patients highest_avg_study = study_name return (highest_avg_study, highest_avg)```This function takes a list of dictionaries, where each dictionary represents a study with its name and a list of patient counts per month. It iterates through each study, calculates the average number of patients for that study, and keeps track of the study with the highest average. Finally, it returns a tuple containing the study name with the highest average and the average number of patients for that study.

answer:Here's the Python function to calculate the weighted average of a list of numbers:```pythonfrom typing import List, Optionaldef weighted_average(numbers: List[float], weights: List[float]) -> Optional[float]: if len(numbers) != len(weights): return None total_weight = sum(weights) weighted_sum = sum(num * weight for num, weight in zip(numbers, weights)) if total_weight == 0: return None return weighted_sum / total_weight```This function takes two lists, `numbers` and `weights`, as input. It first checks if the lengths of the two lists are equal. If not, it returns `None`.If the lengths are equal, it calculates the total weight by summing up all the weights in the `weights` list. It then calculates the weighted sum by multiplying each number with its corresponding weight and summing up the products.If the total weight is zero (all weights are zero), it returns `None` as the weighted average is undefined in this case.Finally, it returns the weighted average by dividing the weighted sum by the total weight.

answer:def count_onions(memories): count = 0 for memory in memories: count += memory.lower().split().count("onion") return count

answer:def count_overlapping_conflicts(conflicts, from_date, to_date): from datetime import datetime overlapping_conflicts = 0 for conflict in conflicts: start_date = datetime.strptime(conflict["start_date"], "%Y-%m-%d") end_date = datetime.strptime(conflict["end_date"], "%Y-%m-%d") from_date_obj = datetime.strptime(from_date, "%Y-%m-%d") to_date_obj = datetime.strptime(to_date, "%Y-%m-%d") if (start_date <= to_date_obj) and (end_date >= from_date_obj): overlapping_conflicts += 1 return overlapping_conflicts