2 Consider the sequence of keys (5,16,22,45,2,10,18,30,50,12,1). Draw the result of inserting entries with these keys (in the gi
Juliette [100K]
Answer:
A) (2,4) tree
- Insertion of key 45 makes key unbalanced and this is because it violates the 2,4 tree so we split the node
- insertion of key 10 makes key unbalanced and this is because it violates the 2,4 tree so we split the node
B) Red-black tree
Explanation:
The diagrams for the solutions are attached showing the results of inserting entries
Answer:
The program to this question can be given as:
Program:
#include <stdio.h> //include header file.
int main() //defining main method
{
char i,j; //defining variable
for (i='a'; i<='e'; i++) //outer loop for column
{
for (j='a'; j<='e'; j++) //inner loop for row
{
printf("%c%c\n",i,j); //print value
}
}
return 0;
}
Output:
image.
Explanation:
- In the above C language program, firstly a header file is included. Then the main method is defined in this, a method contains a char variable that is "i and j". This variable is used in for loop, that is used to print the pattern.
- To print the following patter two for loop is used the outer loop is used for print columns and the inner loop prints row.
- In C language to print character, we use "%c" inside a loop print function is used, that prints characters.
Answer:
import pandas as pd #importing pandas library as pd
import matplotlib.pyplot as plt #importing matplotlib.pyplot as plt
pop=pd.read_csv('nycHistPop.csv') #reading the csv file
borough=input('Enter borough name:') #asking the user for borough namme
# image=input('Enter image name:')
# pop['Fraction']=pop[borough]/pop['Total']
# pop.plot(x='Year', y='Fraction')
print("Minimum population",pop[borough].min()) #printing the minimum population of borough
print("Maximum population",pop[borough].max()) #printing the maximum population of borough
print("Average population",pop[borough].mean()) #printing the average population of borough
print("Standard deviation",pop[borough].std()) #printing the standard deviation of borough
# fig=plt.gcf()
# fig.savefig(image)
Explanation: