answer:Here is a Python solution using the built-in sorted function with a lambda function as the key:```pythonmovies = [('Avatar', 2009), ('Titanic', 1997), ('Star Wars: The Force Awakens', 2015)]sorted_movies = sorted(movies, key=lambda movie: movie[1], reverse=True)for movie in sorted_movies: print(movie)```In this code:- The built-in sorted function is used to sort the list 'movies'. The operation is carried out based on the second element of each tuple i.e. the publishing date which is done using a lambda function.- The 'reverse=True' argument in the function call for sorted means that the sorting will be done in descending order.- The final sorted_movies list will hold the movies in reverse chronological order. The for loop at the end prints each movie from this list.Please, replace the print statement with your preferable way to output or use the data. If you want to save the output to a variable just omit the last two lines of code.

answer:To perform exploratory data analysis (EDA) on the digits dataset supplied by Scikit-learn, you need to take a multi-step approach encompassing activities such as data loading, data description and visualization, and featuring engineering.Here's an example of how to execute exploratory data analysis using Python:```python# Import necessary librariesfrom sklearn import datasetsimport pandas as pdimport numpy as npimport matplotlib.pyplot as pltimport seaborn as sns# Load the digits datasetdigits = datasets.load_digits()# Check the keys/variations in the datasetprint(digits.keys())# Visualize the descriptionsprint(digits.DESCR)# Create a dataframe from digits datadf = pd.DataFrame(digits.data, columns=digits.feature_names)# Verify the data inserted correctlyprint(df.head())# Add target and target name columnsdf['target'] = digits.targetdf['target_name'] = df.target.apply(lambda x: digits.target_names[x])# Verify new columns createdprint(df.head())# Statistical summary of the dataprint(df.describe())# Check for null valuesprint(df.isnull().sum())# Count of each class in the datasetprint(df.target_name.value_counts())# Data visualizations# Histogram representation of all numeric datadf.hist(bins=50, figsize=(20,15))plt.show()# Correlation matrixcorr_matrix = df.corr()sns.heatmap(corr_matrix, annot=True, cmap="YlGnBu")plt.show()# Scatter matrix for few featuresfrom pandas.plotting import scatter_matrixattributes = ['mean area', 'mean compactness', 'mean perimeter', 'mean radius']scatter_matrix(df[attributes], figsize=(12, 8))plt.show()```This EDA provides insights about the data and valuable assistance when engineering features in the data extraction stage of a machine learning project, such as:1. Verifying whether the data is inserted correctly and confirming the data distributions.2. Checking the count of each class in the dataset.3. Viewing the statistical summary of the data.4. Looking for null or missing values.5. Producing a scatter matrix for features.6. Making a correlation matrix.Please modify the chosen attributes according to the data and problems you are working with.

answer:Here is the correct version of the function following the requirement:```pythondef count_nums(arr): count = 0 for num in arr: if sum(int(i) for i in str(abs(num))) % 4 == 0: count += 1 return count```To test the function "count_nums": ```pythonprint(count_nums([4, -4, -5, 5, 12, 22, -22])) # it should return 5```Explanation:Sum of digits for each element: 4 (for 4), 4 (for -4), 5 (for -5), 5 (for 5), 3 (for 12), 4 (for 22), 4 (for -22)But, out of them only 4 (for 4), 4 (for -4), 4 (for 22) and 4 (for -22) are divided by 4. So the count is 4.Note:This solution might not be effective for large numbers since we're converting integers to string to iterate over individual digits. An alternative solution would be to use digit manipulation to compute the sum of digits:```pythondef count_nums(arr): def sum_digits(n): n = abs(n) total = 0 while n > 0: n, remainder = divmod(n, 10) total += remainder return total return sum(sum_digits(i) % 4 == 0 for i in arr)```This function treats the input number n as a sequence of digits and repeatedly divvies it up into a quotient and a remainder using the divmod function, accumulating the total sum of digits in the process.

answer:Below is a Java class that will do what you've asked. This class uses a constructor to create an Object of type Macaw with the name, age, and number of phrase attributes. It also contains a method to represent the Macaw object as a string.```javapublic class Macaw { // Variables to store name, age and phrases of the macaw private String name; private int ageInHumanYears; private int noOfPhrases; // Constructor to initialize these variables public Macaw(String name, int ageInHumanYears, int noOfPhrases) { this.name = name; this.ageInHumanYears = ageInHumanYears; this.noOfPhrases = noOfPhrases; } //Methods to get the private values of name, age and phrases public String getName() { return name; } public int getAgeInHumanYears() { return ageInHumanYears; } public int getNoOfPhrases() { return noOfPhrases; } // toString method to print the macaw information @Override public String toString() { return "Name: " + getName() + "nAge in Human Years: " + getAgeInHumanYears() + "nNumber of Distinct Word Phrases: " + getNoOfPhrases(); } public static void main(String[] args) { Macaw polly = new Macaw("Polly", 5, 30); System.out.println(polly); }}```When you run this program, as there is a `main` method also included in the class for testing the class, it will print:```Name: PollyAge in Human Years: 5Number of Distinct Word Phrases: 30```This means a Macaw named "Polly", who is 5 years old in human years, can say 30 different phrases.

answer:You can flip an SVG horizontally by applying a transform scale of '-1,1'. This means you'll flip the image by 180 degrees around the Y-axis.Here's the SVG provided with the transform applied:```html<svg width="32" height="32" viewBox="0 0 32 32" fill="none" xmlns="http://www.w3.org/2000/svg"><g transform="scale(-1, 1) translate(-32, 0)"><path d="M16 30C23.732 30 30 23.732 30 16C30 8.26801 23.732 2 16 2C8.26801 2 2 8.26801 2 16C2 23.732 8.26801 30 16 30ZM16 20C13.7909 20 12 18.2091 12 16C12 13.7909 13.7909 12 16 12C18.2091 12 20 13.7909 20 16C20 18.2091 18.2091 20 16 20Z" fill="#B4ACBC"/><path d="M19.5354 12.4645C18.6305 11.5596 17.3805 11 15.9998 11C15.0969 11 14.2499 11.2393 13.5187 11.658L10.2924 6.01207C9.88168 5.29326 10.1284 4.36866 10.8895 4.04295C12.4581 3.37164 14.1856 3 15.9998 3C19.0504 3 21.8555 4.05073 24.0731 5.81002C24.7221 6.3249 24.7173 7.28249 24.1315 7.86827L19.5354 12.4645ZM12.4643 19.5355C13.3691 20.4404 14.6191 21 15.9998 21C16.9028 21 17.7498 20.7607 18.481 20.3419L21.7072 25.9879C22.118 26.7067 21.8713 27.6313 21.1102 27.9571C19.5415 28.6284 17.8141 29 15.9998 29C12.9493 29 10.1441 27.9493 7.92657 26.19C7.27758 25.6751 7.28233 24.7175 7.86812 24.1317L12.4643 19.5355Z" fill="#F3EEF8"/></g></svg>```This transform scale and translate method rescales and repositions the SVG to ensure it still appears within the same viewbox after being flipped.

answer:The aforementioned Python code has several flaws:1. urlparse doesn't work properly with URLs that don't have scheme (like 'http://' or 'https://'). So 'www.example.com/users' will be wrongly parsed.2. The program only extracts the protocol and path, but it should also deal with the domain, subdomain, and query string.Corrected and extended Python code:```pythonfrom urllib.parse import urlparse, parse_qsdef parse_url(url): if "://" not in url: url = "http://" + url result = urlparse(url) host_parts = result.netloc.split('.') subdomain, domain, tld = '', '', '' if len(host_parts) == 3: subdomain, domain, tld = host_parts elif len(host_parts) == 2: domain, tld = host_parts print("Protocol: ", result.scheme) print("Domain: ", domain + '.' + tld) if subdomain: print("Subdomain: ", subdomain) print("Path: ", result.path) if result.query: print("Query String: ", result.query) print("Parsed Query String: ", parse_qs(result.query))parse_url("www.subdomain.example.com/index.html?product_id=111&user_id=222")```This corrected code also takes care for URLs without 'http://' or 'https://'. It splits the network location (netloc) to identify the domain and subdomain (if any). If there's a query string, it is printed as is, as well as parsed into a dictionary.This code assumes standard domain formats with only one level of subdomain and standard top-level domains (not encompassing country-code second-level domains or long multi-part top-level domains). For comprehensive URL parsing, additional steps or a dedicated library might be required.