HOW TO ADD WEIGHTS TO THE EDGES FROM A DATASET import networkx as nx import pandas as pd import matplotlib.pyplot as plt %matplotlib inline df=pd.read_csv("abc.csv") df G=nx.from_pandas_edgelist(df, source="from",target="to") plt.figure(figsize=(12,12)) nx.draw(G,with_labels=True)

NetworkX graph generators are used to create empty graphs, digraphs, multigraphs and multidigraphs without any nodes or edges. O True O False

Please do not give solution in image format thanku USING JAVA Modify the code to use Arraylist Instead of HashmapCODE:import java.util.ArrayList;import java.util.HashMap;import java.util.List;import java.util.Map;class Student {private String name;private List<String> certificates;public Student(String name) {this.name = name;this.certificates = new ArrayList<>();}public void addCertificate(String certificate) {  certificates.add(certificate);}public boolean hasCertificate(String certificate) {return certificates.contains(certificate);}public String getName() {return name;}}public class CertificateManagement {public static void main(String[] args) {  Map<String, Student> students = new HashMap<>();Student student1 = new Student("John");student1.addCertificate("Java");student1.addCertificate("Python");students.put("John", student1);Student student2 = new Student("Alice");student2.addCertificate("C++");students.put("Alice", student2);Student student3 = new…

explain this code for me please  import cv2 as cv import numpy as np from matplotlib import pyplot as plt def lanesDetection(img):       height = img.shape[0]     width = img.shape[1]     region_of_interest_vertices = [         (200, height), (width/2, height/1.37), (width-300, height)     ]     gray_img = cv.cvtColor(img, cv.COLOR_RGB2GRAY)     edge = cv.Canny(gray_img, 50, 100, apertureSize=3)     cropped_image = region_of_interest(         edge, np.array([region_of_interest_vertices], np.int32))     lines = cv.HoughLinesP(cropped_image, rho=2, theta=np.pi/180,                            threshold=50, lines=np.array([]), minLineLength=10, maxLineGap=30)     image_with_lines = draw_lines(img, lines)       return image_with_lines def region_of_interest(img, vertices):     mask = np.zeros_like(img)       match_mask_color = (255)     cv.fillPoly(mask, vertices, match_mask_color)     masked_image = cv.bitwise_and(img, mask)     return masked_image def draw_lines(img, lines):     img…