Computer Science Project || ISC || Sunrise Days

on December 10, 2025 in computer, isc, sunrise with No comments

Problem 1: Write a program to check a number is Smith or not. [Digits of Smith number when added is equal to sum of digits of prime factors of the number. 27 is Smith number because 2+7=9 and 27=333]

Solution

import java.util.Scanner;

class Smith {
    public static boolean isPrime(int n) {
        if (n <= 1)
            return false;
        for (int i = 2; i <= Math.sqrt(n); i++) {
            if (n % i == 0)
                return false;
        }
        return true;
    }

    public static int sumOfDigit(int n) {
        int sum = 0;
        while (n > 0) {
            sum = sum + n % 10;
            n = n / 10;
        }
        return sum;
    }

    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter a number: ");
        int n = sc.nextInt();
        int k=n, s=0;
        for (int i = 2; i <= n; i++) {
            if (isPrime(i)) {
                while (k % i == 0) {
                    k = k / i;
                    s = s + sumOfDigit(i);
                }
            }
        }
        if (sumOfDigit(n) == s)
            System.out.println(n + " is Smith number");
        else
            System.out.println(n + " is not Smith number");
        sc.close();
    }
}

Output

Enter a number:
27
27 is Smith number

Enter a number:
12
12 is not Smith number

Problem 2: Write a program to check whether a number is Kaprekar. [A Kaprekar number's square can be split into two parts that add up to the original number. 45 is Kaprekar number because 45^2 = 2025 and 20+25=45].

Solution

import java.util.Scanner;

class Kaprekar {
    public static int noOfDigits(int n) {
        int count = 0;
        while (n > 0) {
            count++;
            n = n / 10;
        }
        return count;
    }

    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter a number: ");
        int n = sc.nextInt();
        int c = noOfDigits(n);
        int sq = n * n;
        int l = sq / (int) Math.pow(10, c);
        int r = sq % (int) Math.pow(10, c);
        if (l + r == n)
            System.out.println(n + " is Kaprekar number");
        else
            System.out.println(n + " is not Kaprekar number");
        sc.close();
    }
}

Output

Enter a number:
45
45 is Kaprekar number

Enter a number:
10
10 is not Kaprekar number

Problem 3: Write a program to find out the given number is a ISBN number or not. [ISBN is a 10 digit number where the last digit is a check digit. The check digit is calculated as (10a1+9a2+8a3+7a4+6a5+5a6+4a7+3a8+2*a9)%11 and if the check digit is 10 then it is represented as X]

Solution

import java.util.Scanner;

class ISBN {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter a number: ");
        int n = sc.nextInt();
        int sum = 0;
        int a = n;
        int i = 10;
        while (a > 0) {
            int r = a % 10;
            sum = sum + r * i;
            a = a / 10;
            i--;
        }
        int checkDigit = sum % 11;
        if (checkDigit == 10)
            System.out.println(n + " is ISBN number");
        else
            System.out.println(n + " is not ISBN number");
        sc.close();
    }
}

Output

Enter a number:
950126105537
950126105537 is ISBN number

Enter a number:
950126105538
950126105538 is not ISBN number

Problem 4: Write a program to check whether a number is Disarium. [A Disarium number is a number where the sum of its digits powered with their respective positions is equal to the number itself. 175 is Disarium number because 1^1+7^2+5^3=175]

Solution

import java.util.Scanner;

class Disarium {
    public static int noOfDigits(int n) {
        int count = 0;
        while (n > 0) {
            count++;
            n = n / 10;
        }
        return count;
    }

    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter a number: ");
        int n = sc.nextInt();
        int c = noOfDigits(n);
        int sum = 0;
        int a = n;
        int i = 1;
        while (a > 0) {
            int r = a % 10;
            sum = sum + (int) Math.pow(r, i);
            a = a / 10;
            i++;
        }
        if (sum == n)
            System.out.println(n + " is Disarium number");
        else
            System.out.println(n + " is not Disarium number");
        sc.close();
    }
}

Output

Enter a number:
175
175 is Disarium number

Enter a number:
176
176 is not Disarium number

Problem 5: Write a program to check whether a number is Keith. [A Keith number isis a number that appears in a sequence generated from its own digits, where the sequence starts with the digits of the number, and each new term is the sum of the previous k terms (k being the number of digits). For example, 197 (3 digits) starts a sequence: 1, 9, 7, (1+9+7)=17, (9+7+17)=33, (7+17+33)=57, (17+33+57)=107, (33+57+107)=197; since 197 appears, it's a Keith number.]

Solution

import java.util.Scanner;

class Keith {
    public static int noOfDigits(int n) {
        int count = 0;
        while (n > 0) {
            count++;
            n = n / 10;
        }
        return count;
    }

    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter a number: ");
        int n = sc.nextInt();
        int c = noOfDigits(n);
        int[] arr = new int[c];
        int a = n;
        int i = 0;
        while (a > 0) {
            arr[i] = a % 10;
            a = a / 10;
            i++;
        }
        int sum = 0;
        for (int j = 0; j < c; j++) {
            sum = sum + arr[j];
        }
        while (sum != n) {
            for (int j = 0; j < c - 1; j++) {
                arr[j] = arr[j + 1];
            }
            arr[c - 1] = sum;
            sum = 0;
            for (int j = 0; j < c; j++) {
                sum = sum + arr[j];
            }
        }
        if (sum == n)
            System.out.println(n + " is Keith number");
        else
            System.out.println(n + " is not Keith number");
        sc.close();
    }
}

Output

Enter a number:
197
197 is Keith number

Enter a number:
198
198 is not Keith number

Problem 6: Write a program to generate a Pascal Triangle for n rows. [Pascal's Triangle is a triangular array of the binomial coefficients. The rows of Pascal's Triangle are conventionally enumerated starting with row 0 at the top.]

Solution

import java.util.Scanner;

class PascalTriangle {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter the number of rows: ");
        int n = sc.nextInt();
        int[][] arr = new int[n][n];
        for (int i = 0; i < n; i++) {
            for (int j = 0; j <= i; j++) {
                if (j == 0 || j == i)
                    arr[i][j] = 1;
                else
                    arr[i][j] = arr[i - 1][j - 1] + arr[i - 1][j];
            }
        }
        for (int i = 0; i < n; i++) {
            for (int j = 0; j < n - i - 1; j++) {
                System.out.print(" ");
            }
            for (int j = 0; j <= i; j++) {
                System.out.print(arr[i][j] + " ");
            }
            System.out.println();
        }
        sc.close();
    }
}

Output

Enter the number of rows:
5
    1
   1 1
  1 2 1
 1 3 3 1
1 4 6 4 1

Problem 7: Write a program to find GCD using recursive function. [GCD is the greatest common divisor of two numbers. It is the largest number that divides both numbers without leaving a remainder.]

Solution

import java.util.Scanner;

class GCD {
    public static int gcd(int a, int b) {
        if (b == 0)
            return a;
        else
            return gcd(b, a % b);
    }
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter two numbers: ");
        int a = sc.nextInt();
        int b = sc.nextInt();
        System.out.println("GCD of " + a + " and " + b + " is " + gcd(a, b));
        sc.close();
    }
}

Output

Enter two numbers:
48 18
GCD of 48 and 18 is 6

Problem 8: Write a program to perform Permutation for a given limit and a common factor. [Permutation is an arrangement of all the members of a set into some sequence or order.]

Solution

import java.util.Scanner;

class Permutation {
    public static long fact(int n) {
        if (n == 0)
            return 1;
        else
            return n * fact(n - 1);
    }

    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter the limit: ");
        int n = sc.nextInt();
        System.out.println("Enter the common factor: ");
        int r = sc.nextInt();
        long count = fact(n) / fact(n - r); // n! / (n-k)!)
        System.out.println("Number of permutations where product is divisible by " + r + " is " + count);
        sc.close();
    }
}

Output

Enter the limit:
12
Enter the common factor:
4
Number of permutations where product is divisible by 4 is 11880

Problem 9: Write a program to perform combination for a given limit and a common factor. [Combination is a selection of items from a larger set, where the order of selection does not matter.]

Solution

import java.util.Scanner;

class Combination {
    public static long fact(int n) {
        if (n == 0)
            return 1;
        else
            return n * fact(n - 1);
    }

    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter the limit: ");
        int n = sc.nextInt();
        System.out.println("Enter the common factor: ");
        int r = sc.nextInt();
        long count = fact(n) / (fact(r) * fact(n - r)); // n! / (r! * (n-r)!)
        System.out.println("Number of combinations where product is divisible by " + r + " is " + count);
        sc.close();
    }
}

Output

Enter the limit:
12
Enter the common factor:
4
Number of combinations where product is divisible by 4 is 495

Problem 10: Write a program to generate AP series and print its sum by getting first term, common ratio and no of terms as input.

Solution

import java.util.Scanner;

class APSeries {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter the first term: ");
        int a = sc.nextInt();
        System.out.println("Enter the common difference: ");
        int d = sc.nextInt();
        System.out.println("Enter the number of terms: ");
        int n = sc.nextInt();
        int sum = 0;

        System.out.println("AP series is: ");
        for (int i = 0; i < n; i++) {
            int term = a + i * d;
            System.out.print(term + " ");
            sum += term;
        }
        System.out.println("\nSum of AP series is: " + sum);
        sc.close();
    }
}

Output

Enter the first term:
2
Enter the common difference:
3
Enter the number of terms:
5
AP series is: 2 5 8 11 14 
Sum of AP series is: 40

Problem 11: Write a program to generate GP series and print its sum by getting first term, common ratio and no of terms as input.

Solution

import java.util.Scanner;

class GPSeries {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter the first term: ");
        int a = sc.nextInt();
        System.out.println("Enter the common ratio: ");
        int r = sc.nextInt();
        System.out.println("Enter the number of terms: ");
        int n = sc.nextInt();
        int sum = 0;
        double product = 1;
        System.out.println("GP series is: ");
        for (int i = 0; i < n; i++) {
            int term = (int) (a * Math.pow(r, i));
            System.out.print(term + " ");
            sum += term;
            product *= term;
        }
        System.out.println("\nSum of GP series is: " + sum);
        System.out.println("Product of GP series is: " + product);
        sc.close();
    }
}

Output

Enter the first term:
2
Enter the common ratio:
3
Enter the number of terms:
5
GP series is: 2 6 18 54 162 
Sum of GP series is: 242
Product of GP series is: 1458

Problem 12: Write a program to change a number into a Roman number. [Roman numerals are represented by seven different symbols: I, V, X, L, C, D and M.]

Solution

import java.util.Scanner;

class RomanNumber {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter a number: ");
        int n = sc.nextInt();
        String[] roman = {"M", "CM", "D", "CD", "C", "XC", "L", "XL", "X", "IX", "V", "IV", "I"};
        int[] values = {1000, 900, 500, 400, 100, 90, 50, 40, 10, 9, 5, 4, 1};
        String result = "";
        for (int i = 0; i < values.length; i++) {
            while (n >= values[i]) {
                result += roman[i];
                n -= values[i];
            }
        }
        System.out.println("Roman number is: " + result);
        sc.close();
    }
}

Output

Enter a number:
1987
Roman number is: MCMLXXXVII

Problem 13: Write a program to find denomination of a given amount.

Solution

import java.util.Scanner;

class Denomination {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter the amount: ");
        int amount = sc.nextInt();
        int[] denominations = {1000, 500, 100, 50, 20, 10, 5, 2, 1};
        int[] count = new int[denominations.length];
        for (int i = 0; i < denominations.length; i++) {
            count[i] = amount / denominations[i];
            amount = amount % denominations[i];
        }
        System.out.println("Denomination of " + amount + " is: ");
        for (int i = 0; i < denominations.length; i++) {
            if (count[i] > 0)
                System.out.println(denominations[i] + " x " + count[i]);
        }
        sc.close();
    }
}

Output

Enter the amount:
1234
Denomination of 1234 is: 
1000 x 1
200 x 1
100 x 2
20 x 1
10 x 3
4 x 2

Problem 14: Write a program to swap two strings without using third variable.

Solution

import java.util.Scanner;

class SwapStrings {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.println("Enter the first string: ");
        String str = sc.nextLine();
        System.out.println("Enter the second string: ");
        String str1 = sc.nextLine();
        str = str + str1;
        str1 = str.substring(0, str.length() - str1.length());
        str = str.substring(str1.length());
        System.out.println("After swapping: ");
        System.out.println("First string: " + str);
        System.out.println("Second string: " + str1);
        sc.close();
    }
}

Output

Enter the first string:
Hello
Enter the second string:
World
After swapping: 
First string: World
Second string: Hello

Problem 15: Write a program to display the below pattern

1 A A A A A
2 2 B B B B
3 3 3 C C C
4 4 4 4 D D
5 5 5 5 5 E

Solution

class Pattern {
    public static void main(String[] args) {
        char ch = 'A';
        for (int i = 1; i <= 5; i++) {
            for (int j = 1; j <= i; j++) {
                System.out.print(i + " ");
            }
            for (int k = 1; k <= 5 - i; k++) {
                System.out.print(ch + " ");
            }
            System.out.println();
            ch++;
        }
    }
}

Problem 16: Write a program to enter a natural number and display all possible combinations of consecutive natural numbers that sum up to that number.

Solution

import java.util.Scanner;

class ConsecutiveSum {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.print("Enter a natural number: ");
        int n = sc.nextInt();
        for (int i = 1; i <= n; i++) {
            int sum = 0;
            for (int j = i; j <= n; j++) {
                sum += j;
                if (sum == n) {
                    for (int k = i; k <= j; k++) {
                        System.out.print(k + " ");
                    }
                    System.out.println();
                    break;
                } else if (sum > n) {
                    break;
                }
            }
        }
        sc.close();
    }
}

Output

Enter a natural number: 15
1 2 3 4 5
4 5 6 
7 8 
15

Problem 17: Write a program to display the below pattern

11
12 22
13 23 33
14 24 34 44
15 25 35 45 55

Solution

import java.util.Scanner;

class Pattern {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.print("Enter the number of rows: ");
        int n = sc.nextInt();
        for (int i = 1; i <= n; i++) {
            for (int j = 1; j <= i; j++) {
                System.out.print(j + "" + i + " ");
            }
            System.out.println();
        }
        sc.close();
    }
}

Problem 18: Write a program to display the below pattern

*************
*           *
*           *
*           *
*           *
*           *
*           *
*           *
*           *
*************

Solution

class Pattern {
    public static void main(String[] args) {
        int n = 10;
        for (int i = 1; i <= n; i++) {
            for (int j = 1; j <= n; j++) {
                if (i == 1 || i == n || j == 1 || j == n)
                    System.out.print("*");
                else
                    System.out.print(" ");
            }
            System.out.println();
        }
    }
}

Problem 19: Write a program to check whether given pair of numbers are Twin Prime. [Twin primes are pairs of prime numbers that have a difference of 2.]

Solution

import java.util.Scanner;

class TwinPrime {
    public static boolean isPrime(int n) {
        if (n <= 1)
            return false;
        for (int i = 2; i <= Math.sqrt(n); i++) {
            if (n % i == 0)
                return false;
        }
        return true;
    }
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.print("Enter the first number: ");
        int n1 = sc.nextInt();
        System.out.print("Enter the second number: ");
        int n2 = sc.nextInt();
        if (isPrime(n1) && isPrime(n2) && Math.abs(n1 - n2) == 2)
            System.out.println(n1 + " and " + n2 + " are Twin Primes.");
        else
            System.out.println(n1 + " and " + n2 + " are not Twin Primes.");
        sc.close();
    }
}

Output

Enter the first number:
3
Enter the second number:
5
3 and 5 are Twin Primes.

Problem 20: Write a program to merge two sorted arrays.

Solution

import java.util.Arrays;
import java.util.Scanner;

class MergeSortedArrays {
    public static void main(String[] args) {
        Scanner sc = new Scanner(System.in);
        System.out.print("Enter the size of the first array: ");
        int n = sc.nextInt();
        int[] arr1 = new int[n];
        System.out.print("Enter the elements of the first array: ");
        for (int i = 0; i < n; i++)
            arr1[i] = sc.nextInt();
        System.out.print("Enter the size of the second array: ");
        int m = sc.nextInt();
        int[] arr2 = new int[m];
        System.out.print("Enter the elements of the second array: ");
        for (int i = 0; i < m; i++)
            arr2[i] = sc.nextInt();
        int[] mergedArray = new int[n + m];
        int i = 0, j = 0, k = 0;
        while (i < n && j < m) {
            if (arr1[i] < arr2[j])
                mergedArray[k++] = arr1[i++];
            else
                mergedArray[k++] = arr2[j++];
        }
        while (i < n)
            mergedArray[k++] = arr1[i++];
        while (j < m)
            mergedArray[k++] = arr2[j++];
        System.out.println("Merged sorted array: " + Arrays.toString(mergedArray));
        sc.close();
    }
}

Output

Enter the size of the first array:
3
Enter the elements of the first array: 1 3 5
Enter the size of the second array:
3
Enter the elements of the second array: 2 4 6
Merged sorted array: [1, 2, 3, 4, 5, 6]

Data Visualisation with Matplotlib || Fresco Play || 56869

on May 23, 2025 in 56869, dataviz, frescoplay, matplotlib, python with No comments

Data Visualisation with Matplotlib - 56869

Matplotlib-1 - My First Plot

Task1

Create a function named test_the_plot.
Create a figure of size 12 inches in width, and 6 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Create a list t with values [7, 14, 21, 28, 35]
Create a list d with values [i*6 for i in t]
Draw a line, by plotting t values on X-Axis and d values on Y-Axis. Use the plot function. Label the line as d = 6t.
Label X-Axis as time (seconds).
Label Y-Axis as distance (meters).
Set Title as Time vs Distance Covered.
Limit data points on X-Axis from 0 to 40.
Limit data points on Y-Axis from 0 to 220.
Add a legend.
return the figure object

Note: The results of preliminary validation doesn't impact final scoring. In-depth scorings are done at a later stage.

Once you are in the Web IDE:

Open prog.py in the jupyter lab the file and start your coding by following the instructions given above.
Once you are done with the solution , then run the following commands in the terminal to check your solutions. Click File -> New -> Terminal, run the following commands

python3 prog.py

After running the test cases, click the submit button and click on Submit Test to end the assessment.

Note - Here Rough_Work.ipynb can be used for rough work to get the solutions

Solution

import numpy as np
import matplotlib.pyplot as plt


def test_the_plot():
    fig = plt.figure(figsize=(12, 6))
    ax = fig.add_subplot(111)
    t = [7, 14, 21, 28, 35]
    d = [i * 6 for i in t]
    ax.plot(t, d, label='d = 6t')
    ax.set_xlabel('time (seconds)')
    ax.set_ylabel('distance (meters)')
    ax.set_title('Time vs Distance Covered')
    ax.set_xlim(0, 40)
    ax.set_ylim(0, 220)
    ax.legend("My First Plot")
    return fig

# Note: Do Not modify the below code
if __name__ == '__main__':
    import sys
    import subprocess
    subprocess.check_call(
        [sys.executable, "-m", "pip", "install", 'test_plot1-0.2-py3-none-any.whl'], stdout=subprocess.DEVNULL)
    from test_plot1 import matplotlib1
    usr_fig = test_the_plot()
    matplotlib1.save_answer(usr_fig)

Matplotlib-2 - Scatter Plots

Task1

Create a function named sine_wave_plot.
Create a figure of size 13 inches in width, and 4 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Create a numpy array arr_t with 250 values between 0.0 and 3.0. Use the 'linspace' method to generate 250 values.
Create a numpy array arr_v, such that arr_v = np.sin(2.5*np.pi*arr_t).
Pass arr_t and arr_v as variables to plot function and draw a red line passing through the selected 250 points. Label the line as sin(arr_t).
Label X-Axis as Time (seconds).
Label Y-Axis as Voltage (mv).
Set Title as Sine Wave.
Limit data on X-Axis from 0 to 2.
Limit data on Y-Axis from -1 to 1.
Mark major ticks on X-Axis at 0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, and 2.0.
Mark major ticks on Y-Axis at -1, 0, and 1.
Add a grid, whose linestyle is dashdot.
Add a legend.
return the figure object

Task2

Create a function named multi_curve_plot.
Create a figure of size 13 inches in width, and 4 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Create a numpy array arr_x with 25 values between 0.0 and 7.0. Use the 'linspace' method to generate 25 values.
Create three numpy arrays arr_y1, arr_y2 and arr_y3, using the expressions arr_y1 = arr_x, arr_y2 = arr_x**2 and arr_y3 = arr_x**3 respectively.
Draw a green colored line passing through arr_x and arr_y1, using the plot function. Mark the 25 data points on the line as upward pointed triangles. Label the line as y = arr_x.
Draw a blue colored line passing through arr_x and arr_y2, using the plot function. Mark the 25 data points on the line as squares. Label the line as y = arr_x**2.
Draw a red colored line passing through arr_x and arr_y3, using the plot function. Mark the 25 data points on the line as circles.
Label the line as y = arr_x**3.
Label X-Axis as arr_x.
Label Y-Axis as f(arr_x).
Set Title as Linear, Quadratic, & Cubic Equations.
Add a legend.
return the figure object

Task3

Create a function named scatter_plot.
Create a figure of size 13 inches in width, and 4 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Consider the list car_sales = [40, 65, 70, 40, 55, 60, 75, 60, 80, 95, 96, 105]. It represents the number of cars sold by a Company 'X' in each month of 2021, starting from January, 2021.
Create a list months containing numbers from 1 to 12.
Draw a scatter plot with variables months and car_sales as arguments. Mark the data points in green color. Use the scatter function for plotting.Label the points as car sales.
Limit data on X-Axis from 0 to 13.
Limit data on Y-Axis from 10 to 110.
Mark ticks on X-Axis at 1, 3, 5, 7, 9, and 11.
Label the X-Axis ticks as January, March, May, July, September, and November respectively.
Label X-Axis as Months
Label Y-Axis as No. of Cars Sold
Set Title as "Cars Sold by Company 'Z' in 2021".
Add a legend.
return the figure object

Note: The results of preliminary validation doesn't impact final scoring. In-depth scorings are done at a later stage.

Once you are in the Web IDE:

Open prog.py in the jupyter lab the file and start your coding by following the instructions given above.
Once you are done with the solution , then run the following commands in the terminal to check your solutions. Click File -> New -> Terminal, run the following commands
```
python3 prog.py
```
After running the test cases, click the submit button and click on Submit Test to end the assessment.

Note - Here Rough_Work.ipynb can be used for rough work to get the solutions

Solution

import numpy as np
import matplotlib.pyplot as plt


def sine_wave_plot():

    # Write your functionality below
    fig = plt.figure(figsize=(13, 4))
    ax = fig.add_subplot(111)
    arr_t = np.linspace(0.0, 3.0, num = 250)
    arr_v = np.sin(2.5 * np.pi * arr_t)
    ax.plot(arr_t, arr_v, label="sin(arr_t)")
    ax.set_xlabel("Time (seconds)")
    ax.set_ylabel("Voltage (mv)")
    ax.set_title("Sine Wave")
    ax.set_xlim(0, 2)
    ax.set_ylim(-1, 1)
    ax.set_xticks([0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0])
    ax.set_yticks([-1, 0, 1])
    ax.grid(linestyle="dashdot")
    ax.legend(["Voltage Speed"])
    return fig


def multi_curve_plot():

    # Write your functionality below
    fig = plt.figure(figsize=(13, 4))
    ax = fig.add_subplot(111)
    arr_x = np.linspace(0.0, 7.0, num = 25)
    arr_y1 = arr_x
    arr_y2 = arr_x ** 2
    arr_y3 = arr_x ** 3

    ax.plot(arr_x, arr_y1, color="green", marker="^", label ="y = arr_x")
    ax.plot(arr_x, arr_y2, color="blue", marker="s", label ="y = arr_x**2")
    ax.plot(arr_x, arr_y3, color="red", marker="o", label ="y = arr_x**3")
    ax.set_xlabel("arr_x")
    ax.set_ylabel("f(arr_x)")
    ax.set_title("Linear, Quadratic, & Cubic Equations")
    ax.legend(["Linear", "Quadratic", "Cubic"])
    return fig



def scatter_plot():

    # Write your functionality below
    fig = plt.figure(figsize=(13, 4))
    ax = fig.add_subplot(111)
    car_sales = [40, 65, 70, 40, 55, 60, 75, 60, 80, 95, 96, 105]
    months = np.array(range(1, 13))
    ax.scatter(months, car_sales, color="green", label="car sales")
    ax.set_xlim(0, 13)
    ax.set_ylim(10, 110)
    ax.set_xticks(np.array(range(1, 13, 2)), ["January", "March", "May", "July", "September", "November"])
    ax.set_xlabel("Months")
    ax.set_ylabel("No. of Cars Sold")
    ax.set_title("Cars Sold by Company 'Z' in 2021")
    ax.legend(["Count of Cars Sold"])
    return fig


# Note: Do Not modify the below code
if __name__ == '__main__':
    import sys
    import subprocess
    subprocess.check_call(
        [sys.executable, "-m", "pip", "install", 'test_plot2-0.1-py3-none-any.whl'], stdout=subprocess.DEVNULL)
    from test_plot2 import matplotlib2
    usr_fig1 = sine_wave_plot()
    usr_fig2 = multi_curve_plot()
    usr_fig3 = scatter_plot()
    matplotlib2.save_answer(usr_fig1, usr_fig2, usr_fig3)

Matplotlib-3 - Bar Plots

Task1

Create a function named barplot_of_iris_sepal_length.
Create a figure of size 9 inches in width, and 7 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Define a list species, with elements ['setosa', 'versicolor', 'virginica'].
Define a list index, with values [0.4, 1.4, 2.4].
Define another list sepal_len with values [6.01, 6.94, 7.69]. These values represent the mean sepal length of iris flowers belonging to three species.
Draw a bar plot using the bar function, such that the height of each vertical bar displays the sepal length of a species label it as Sepal Length.
Use index and sepal_len as variables. Set bar width as 0.4, color as blue, and border color of the bar as red.
Label X-Axis as Species.
Label Y-Axis as Sepal Length (cm).
Set Title as Mean Sepal Length of Iris Species.
Limit X-Axis from 0 to 3.
Limit Y-Axis from 0 to 9.
Set ticks on X-Axis at 0.4, 1.4, and 2.4.
Set X-Axis tick labels to ['setosa', 'versicolor', 'virginica'].
Add a legend.
return the figure object.

Task2

Create a function named barplot_of_iris_measurements.
Create a figure of size 9 inches in width, and 7 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Define the following lists:
sepal_len = [6.01, 6.94, 7.59]
sepal_wd = [4.42, 3.77, 3.97]
petal_len = [2.46, 5.26, 6.55]
petal_wd = [1.24, 2.33, 3.03]
species = ['setosa', 'versicolor', 'virginica']
species_index1 = [0.7, 1.7, 2.7]
species_index2 = [0.9, 1.9, 2.9]
species_index3 = [1.1, 2.1, 3.1]
species_index4 = [1.3, 2.3, 3.3]
Draw vertical bars showing the mean sepal length of a species. Set the color of the bars to m, boundary line color to grey, width of bars as 0.2, and label it as Sepal Length. Use bar with species_index1 and sepal_len.
Draw vertical bars showing mean sepal length of a species. Set the color of the bars to y, boundary line color to grey, width of bars as 0.2, and label it as Sepal Width. Use bar with species_index2 and sepal_wd.
Draw vertical bars showing mean sepal length of a species. Set the color of the bars to c, boundary line color to grey, width of bars as 0.2, and label it as Petal Length. Use bar with species_index3 and petal_len.
Draw vertical bars showing mean sepal length of a species. Set the color of the bars to orange, boundary line color to grey, width of bars as 0.2, and label it as Petal Width. Use bar with species_index4 and petal_wd.
Label X-Axis as Species.
Label Y-Axis as Iris Measurements (cm).
Set Title as Mean Measurements of Iris Species.
Limit X-Axis from 0.5 to 3.5 .
Limit Y-Axis from 0 to 10.
Mark major ticks on X-Axis at 1.0, 2.0, and 3.0.
Label the major ticks on X-Axis as setosa, versicolor and virginica respectively.
Add a legend.
return the figure object.

Task3

Create a function named hbarplot_of_iris_petal_length.
Create a figure of size 15 inches in width, and 5 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Define a list species, with elements ['setosa', 'versicolor', 'virginica'].
Define a list index, with values [0.1, 1.1, 2.1].
Define another list petal_len with values [2.67, 5.49, 6.37]. These values represent the mean petal length of iris flowers belonging to three species.
Draw a horizontal bar plot using barh function, such that the width of each bar display the petal length of a species and label it as Petal Length.
Use index and petal_len as variables. Set bar height as 0.4, color as m, and border color of the bar as c.
Label Y-Axis as Species
Label X-Axis as `Petal Length (cm).
Set Title as Mean Petal Length of Iris Species.
Mark major ticks on Y-Axis at 0.10, 1.10 and 2.10.
Label the major ticks on Y-Axis as setosa, versicolor and virginica respectively.
Add a legend.
return the figure object.

Note: The results of preliminary validation doesn't impact final scoring. In-depth scorings are done at a later stage.

Once you are in the Web IDE:

Open prog.py in the jupyter lab the file and start your coding by following the instructions given above.
Once you are done with the solution , then run the following commands in the terminal to check your solutions. Click File -> New -> Terminal, run the following commands
```
python3 prog.py
```
After running the test cases, click the submit button and click on Submit Test to end the assessment.

Note - Here Rough_Work.ipynb can be used for rough work to get the solutions

Solution

import numpy as np
import matplotlib.pyplot as plt


def barplot_of_iris_sepal_length():

    # Write your functionality below
    fig = plt.figure(figsize=(9, 7))
    ax = fig.add_subplot(111)
    species = ['setosa', 'versicolor', 'virginica']
    index = [0.4, 1.4, 2.4]
    sepal_len = [6.01, 6.94, 7.69]
    ax.bar(index, sepal_len, label="Sepal Length", width=0.4, color="blue", edgecolor="red")
    ax.set_xlabel("Species")
    ax.set_ylabel("Sepal Length (cm)")
    ax.set_title("Mean Sepal Length of Iris Species")
    ax.set_xlim(0, 3)
    ax.set_ylim(0, 9)
    ax.set_xticks(index)
    ax.set_xticklabels(species)
    ax.legend(["Sepal Length"])
    return fig


def barplot_of_iris_measurements():

    # Write your functionality below
    fig = plt.figure(figsize=(9, 7))
    ax = fig.add_subplot(111)
    sepal_len = [6.01, 6.94, 7.59]
    sepal_wd = [4.42, 3.77, 3.97]
    petal_len = [2.46, 5.26, 6.55]
    petal_wd = [1.24, 2.33, 3.03]
    species = ['setosa', 'versicolor', 'virginica']
    species_index1 = [0.7, 1.7, 2.7]
    species_index2 = [0.9, 1.9, 2.9]
    species_index3 = [1.1, 2.1, 3.1]
    species_index4 = [1.3, 2.3, 3.3]

    ax.bar(species_index1, sepal_len, color="m", edgecolor="grey", width=0.2, label="Sepal Length")
    ax.bar(species_index2, sepal_wd, color="y", edgecolor="grey", width=0.2, label="Sepal Width")
    ax.bar(species_index3, petal_len, color="c", edgecolor="grey", width=0.2, label="Petal Length")
    ax.bar(species_index4, petal_wd, color="orange", edgecolor="grey", width=0.2, label="Petal Width")
    ax.set_xlabel("Species")
    ax.set_ylabel("Iris Measurements (cm)")
    ax.set_title("Mean Measurements of Iris Species")
    ax.set_xlim(0.5, 3.5)
    ax.set_ylim(0, 10)
    ax.set_xticks([1.0, 2.0, 3.0])
    ax.set_xticklabels(species)
    ax.legend(["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"])

    return fig


def hbarplot_of_iris_petal_length():

    # Write your functionality below
    fig = plt.figure(figsize=(15, 5))
    ax = fig.add_subplot(111)
    species = ['setosa', 'versicolor', 'virginica']
    index = [0.1, 1.1, 2.1]
    petal_len = [2.67, 5.49, 6.37]

    ax.barh(index, petal_len, height=0.4, label="Petal Length", color="m", edgecolor="c")
    ax.set_xlabel("Species")
    ax.set_ylabel("Petal Length (cm)")
    ax.set_title("Mean Petal Length of Iris Species")
    ax.set_yticks(index)
    ax.set_yticklabels(species)
    ax.legend(["Petal Length"])

    return fig


# Note: Do Not modify the below code
if __name__ == '__main__':
    import sys
    import subprocess
    subprocess.check_call(
        [sys.executable, "-m", "pip", "install", 'test_plot3-0.1-py3-none-any.whl'], stdout=subprocess.DEVNULL)
    from test_plot3 import matplotlib3
    usr_fig1 = barplot_of_iris_sepal_length()
    usr_fig2 = barplot_of_iris_measurements()
    usr_fig3 = hbarplot_of_iris_petal_length()
    matplotlib3.save_answer(usr_fig1, usr_fig2, usr_fig3)

Matplotlib-4 - Histograms and Box Plots

Task1

Create a function named hist_of_a_sample_normal_distribution.
Create a figure of size 9 inches in width, and 7 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Set random seed to 100 using the expression np.random.seed(100).
Create a normal distribution dist_arr of 1000 values, with mean 35 and standard deviation 3.0. Use np.random.randn.
Draw a histogram of dist_arr with 35 bins. Use the hist function.
Label X-Axis as dist_arr
Label Y-Axis as Bin Count
Set Title as Histogram of a Single Dataset
return the figure object.

Task2

Create a function named boxplot_of_four_normal_distribution.
Create a figure of size 9 inches in width, and 7 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Set random seed to 100 using the expression np.random.seed(100).
Create a normal distribution arr_1 of 2000 values, with mean 35 and standard deviation 6.0. Use np.random.randn.
Create a normal distribution arr_2 of 2000 values, with mean 25 and standard deviation 4.0. Use np.random.randn.
Create a normal distribution arr_3 of 2000 values, with mean 45 and standard deviation 8.0. Use np.random.randn.
Create a normal distribution arr_4 of 2000 values, with mean 55 and standard deviation 10.0. Use np.random.randn.
Create a list labels with elements ['arr_1', 'arr_2', 'arr_3', 'arr_4].
Draw a Boxplot arr_1, arr_2, arr_3, arr_4 with notches and label it using the labels list. Use the boxplot function.
Choose o symbol for outlier, and fill color inside boxes by setting patch_artist argument to True.
Label X-Axis as Dataset
Label Y-Axis as Value
Set Title as Box plot of Multiple Datasets
return the figure object.

Note: The results of preliminary validation doesn't impact final scoring. In-depth scorings are done at a later stage.

Once you are in the Web IDE:

Open prog.py in the jupyter lab the file and start your coding by following the instructions given above.
Once you are done with the solution , then run the following commands in the terminal to check your solutions. Click File -> New -> Terminal, run the following commands
```
python3 prog.py
```
After running the test cases, click the submit button and click on Submit Test to end the assessment.

Note - Here Rough_Work.ipynb can be used for rough work to get the solutions

Solution

import numpy as np
import matplotlib.pyplot as plt


def hist_of_a_sample_normal_distribution():

    # Write your functionality below
    fig = plt.figure(figsize=(9,7))
    ax = fig.add_subplot(111)
    np.random.seed(100)
    dist_arr = np.random.randn(1000) * 3.0 + 35
    ax.hist(dist_arr, bins=35)
    ax.set_xlabel("dist_arr")
    ax.set_ylabel("Bin Count")
    ax.set_title("Histogram of a Single Dataset")
    return fig


def boxplot_of_four_normal_distribution():

    # Write your functionality below
    fig = plt.figure(figsize=(9,7))
    ax = fig.add_subplot(111)
    np.random.seed(100)
    arr_1 = np.random.randn(2000) * 6.0 + 35
    arr_2 = np.random.randn(2000) * 4.0 + 25
    arr_3 = np.random.randn(2000) * 8.0 + 45
    arr_4 = np.random.randn(2000) * 10.0 + 55
    elements = ['arr_1', 'arr_2', 'arr_3', 'arr_4']
    ax.boxplot([arr_1, arr_2, arr_3, arr_4], labels=elements, patch_artist=True, sym='o')
    ax.set_xlabel("Dataset")
    ax.set_ylabel("Value")
    ax.set_title("Box plot of Multiple Datasets")
    return fig


# Note: Do Not modify the below code
if __name__ == '__main__':
    import sys
    import subprocess
    subprocess.check_call(
        [sys.executable, "-m", "pip", "install", 'test_plot4-0.1-py3-none-any.whl'], stdout=subprocess.DEVNULL)
    from test_plot4 import matplotlib4
    usr_fig1 = hist_of_a_sample_normal_distribution()
    usr_fig2 = boxplot_of_four_normal_distribution()
    matplotlib4.save_answer(usr_fig1, usr_fig2)

Matplotlib-5 - Applying Styles

Task1

Create a function named generate_plot_with_style1.
Generate the following barplot with 'ggplot' style. Use 'with' to apply the style to the code generating the barplot.
Create a figure of size 9 inches in width, and 7 inches in height. Name it as fig.
Create an axis, associated with figure fig, using add_subplot. Name it as ax.
Define the following lists
sepal_len = [6.01, 6.94, 7.59]
sepal_wd = [4.42, 3.77, 3.97]
petal_len = [2.46, 5.26, 6.55]
petal_wd = [1.24, 2.33, 3.03]
species = ['setosa', 'versicolor', 'virginica']
species_index1 = [0.8, 1.8, 2.8]
species_index2 = [1.0, 2.0, 3.0]
species_index3 = [1.2, 2.2, 3.2]
species_index4 = [1.4, 2.4, 3.4]
Draw vertical bars showing mean sepal length of a species. Set width of the bars as 0.2, and label it as Sepal Length. Use bar with species_index1 and sepal_len.
Draw vertical bars showing mean sepal length of a species. Set width of bars as 0.2 and label it as Sepal Width. Use bar with species_index2 and sepal_wd.
Draw vertical bars showing mean sepal length of a species. Set width of bars as 0.2 and label it as Petal Length. Use bar with species_index3 and petal_len.
Draw vertical bars showing mean sepal length of a species. Set width of bars as 0.2 and label it as Petal Width. Use bar with species_index4 and petal_wd.
Label X-Axis as Species.
Label Y-Axis as Iris Measurements (cm).
Set Title as Mean Measurements of Iris Species.
Limit X-Axis from 0.5 to 3.7.
Limit Y-Axis from 0 to 10.
Mark major ticks on X-Axis at 1.0, 2.0, and 3.0.
Label the major ticks on X-Axis as setosa, versicolor, and virginica respectively.
Add a legend.
return the figure object.

Task2

Create a function named generate_plot_with_style2.
Regenerate the barplot defined in 'generate_plot_with_style1' using 'seaborn-colorblind' style. Use 'with' for applying the style.
Limit X-Axis from 0.5 to 3.5.
return the figure object.

Task3

Create a function named generate_plot_with_style3.
Regenerate the barplot defined in 'generate_plot_with_style1' using 'grayscale' style. Use 'with' for applying the style.
Limit X-Axis from 0.5 to 3.5.
return the figure object.

Note: The results of preliminary validation doesn't impact final scoring. In-depth scorings are done at a later stage.

Once you are in the Web IDE:

Open prog.py in the jupyter lab the file and start your coding by following the instructions given above.
Once you are done with the solution , then run the following commands in the terminal to check your solutions. Click File -> New -> Terminal, run the following commands
```
python3 prog.py
```
After running the test cases, click the submit button and click on Submit Test to end the assessment.

Note - Here Rough_Work.ipynb can be used for rough work to get the solutions

Solution

import numpy as np
import matplotlib.pyplot as plt


def generate_plot_with_style1():

    # Write your functionality below
    fig = None
    sepal_len = [6.01, 6.94, 7.59]
    sepal_wd = [4.42, 3.77, 3.97]
    petal_len = [2.46, 5.26, 6.55]
    petal_wd = [1.24, 2.33, 3.03]
    species = ['setosa', 'versicolor', 'virginica']
    species_index1 = [0.8, 1.8, 2.8]
    species_index2 = [1.0, 2.0, 3.0]
    species_index3 = [1.2, 2.2, 3.2]
    species_index4 = [1.4, 2.4, 3.4]
    with plt.style.context('ggplot'):
        fig = plt.figure(figsize=(9, 7))
        ax = fig.add_subplot(111)
        ax.set(title="Mean Measurements of Iris Species", xlabel="Species", ylabel="Iris Measurements (cm)")
        ax.bar(species_index1, sepal_len, width=0.2, label="Sepal Length")
        ax.bar(species_index2, sepal_wd, width=0.2, label="Sepal Width")
        ax.bar(species_index3, petal_len, width=0.2, label="Petal Length")
        ax.bar(species_index4, petal_wd, width=0.2, label="Petal Width")
        ax.set_xlim(0.5, 3.7)
        ax.set_ylim(0, 10)
        ax.set_xticks([1.0, 2.0, 3.0])
        ax.set_xticklabels(species)
        ax.legend(["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"])
    return fig


def generate_plot_with_style2():

    # Write your functionality below
    fig = None
    sepal_len = [6.01, 6.94, 7.59]
    sepal_wd = [4.42, 3.77, 3.97]
    petal_len = [2.46, 5.26, 6.55]
    petal_wd = [1.24, 2.33, 3.03]
    species = ['setosa', 'versicolor', 'virginica']
    species_index1 = [0.8, 1.8, 2.8]
    species_index2 = [1.0, 2.0, 3.0]
    species_index3 = [1.2, 2.2, 3.2]
    species_index4 = [1.4, 2.4, 3.4]
    with plt.style.context('seaborn-colorblind'):
        fig = plt.figure(figsize=(9, 7))
        ax = fig.add_subplot(111)
        ax.set(title="Mean Measurements of Iris Species", xlabel="Species", ylabel="Iris Measurements (cm)")
        ax.bar(species_index1, sepal_len, width=0.2, label="Sepal Length")
        ax.bar(species_index2, sepal_wd, width=0.2, label="Sepal Width")
        ax.bar(species_index3, petal_len, width=0.2, label="Petal Length")
        ax.bar(species_index4, petal_wd, width=0.2, label="Petal Width")
        ax.set_xlim(0.5, 3.5)
        ax.set_ylim(0, 10)
        ax.set_xticks([1.0, 2.0, 3.0])
        ax.set_xticklabels(species)
        ax.legend(["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"])

    return fig


def generate_plot_with_style3():

    # Write your functionality below
    fig = None
    sepal_len = [6.01, 6.94, 7.59]
    sepal_wd = [4.42, 3.77, 3.97]
    petal_len = [2.46, 5.26, 6.55]
    petal_wd = [1.24, 2.33, 3.03]
    species = ['setosa', 'versicolor', 'virginica']
    species_index1 = [0.8, 1.8, 2.8]
    species_index2 = [1.0, 2.0, 3.0]
    species_index3 = [1.2, 2.2, 3.2]
    species_index4 = [1.4, 2.4, 3.4]
    with plt.style.context('grayscale'):
        fig = plt.figure(figsize=(9, 7))
        ax = fig.add_subplot(111)
        ax.set(title="Mean Measurements of Iris Species", xlabel="Species", ylabel="Iris Measurements (cm)")
        ax.bar(species_index1, sepal_len, width=0.2, label="Sepal Length")
        ax.bar(species_index2, sepal_wd, width=0.2, label="Sepal Width")
        ax.bar(species_index3, petal_len, width=0.2, label="Petal Length")
        ax.bar(species_index4, petal_wd, width=0.2, label="Petal Width")
        ax.set_xlim(0.5, 3.5)
        ax.set_ylim(0, 10)
        ax.set_xticks([1.0, 2.0, 3.0])
        ax.set_xticklabels(species)
        ax.legend(["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"])

    return fig


# Note: Do Not modify the below code
if __name__ == '__main__':
    import sys
    import subprocess
    subprocess.check_call(
        [sys.executable, "-m", "pip", "install", 'test_plot5-0.1-py3-none-any.whl'], stdout=subprocess.DEVNULL)
    from test_plot5 import matplotlib5
    usr_fig1 = generate_plot_with_style1()
    usr_fig2 = generate_plot_with_style2()
    usr_fig3 = generate_plot_with_style3()
    matplotlib5.save_answer(usr_fig1, usr_fig2, usr_fig3)

Matplotlib-6 - Multiple Plots

Task1

Create a function named generate_figure1.
Define a numpy array 'x' with expression 'np.arange(0.0, 10.0, 0.01)'.
Define another numpy array 'arr_s1' with expression 'np.sin(3*np.pi*x)'
Define one more numpy array 'arr_s2' with expression 'np.sin(6*np.pi*x)'.
Create a figure of size 12 inches in width, and 7 inches in height. Name it as fig.
Create an axes, using plt.subplot function. Name it as axes1. The subplot must point to the first virtual grid created by 2 rows and 1 column. Set 'title' argument to 'Sin(3*pi*x)'.
Draw a line plot of 'x' and 'arr_s1' using the 'plot' function on 'axes1`.
Create another axes, using the plt.subplot function. Name it as axes2. The subplot must point to the second virtual grid created by 2 rows and 1 column. Set 'title' argument to 'Sin(6*pi*x)'. Set 'sharex' argument to 'axes1' and 'sharey' argument to 'axes1'.
Draw a line plot of 'x' and 'arr_s2' using the 'plot' function on 'axes2`.
return the figure object

Task2

Create a function named generate_figure2.
Set random seed to 1500 using the expression 'np.random.seed(1500)'.
Define a numpy array 'x' with expression 'np.random.rand(10)'.
Define another numpy array 'y' with expression 'np.random.rand(10)'.
Define one more numpy array 'z' with expression 'np.sqrt(x**2 + y**2)'.
Create a figure of size 9 inches in width, and 7 inches in height. Name it as fig.
Create an axes, using plt.subplot function. Name it as axes1. The subplot must point to the first virtual grid created by 2 rows and 2 columns. Set 'title' argument to 'Scatter plot with Diamond Markers'.
Draw a scatter plot of 'x' and 'y' using 'scatter' function on 'axes1`. Set argument 's' to 80, 'c' to z and 'marker' to 'd'.
Add ticks on X-Axis at 0.0, 0.5, 1.0, 1.5 and ticks on Y-Axis at -0.2, 0.2, 0.6, 1.0 respectively
Create an axes, using plt.subplot function. Name it as axes2. The subplot must point to the Second virtual grid created by 2 rows and 2 columns. Set 'title' argument to 'Scatter plot with Circle Markers'.
Draw a scatter plot of 'x' and 'y' using 'scatter' function on 'axes2`. Set argument 's' to 80, 'c' to 'z' and 'marker' to 'o'.
Add ticks on X-Axis at 0.0, 0.5, 1.0, 1.5 and ticks on Y-Axis at -0.2, 0.2, 0.6, 1.0 respectively.
Create an axes, using plt.subplot function. Name it as axes3. The subplot must point to the Third virtual grid created by 2 rows and 2 columns. Set 'title' argument to 'Scatter plot with Plus Markers'.
Draw a scatter plot of 'x' and 'y' using 'scatter' function on 'axes3`. Set argument 's' to 80, 'c' to 'z' and 'marker' to '+'.
Add ticks on X-Axis at 0.0, 0.5, 1.0, 1.5 and ticks on Y-Axis at -0.2, 0.2, 0.6, 1.0 respectively.
Create an axes, using plt.subplot function. Name it as axes4. The subplot must point to the Fourth virtual grid created by 2 rows and 2 columns. Set 'title' argument to 'Scatter plot with Upper Triangle Markers'.
Draw a scatter plot of 'x' and 'y' using 'scatter' function on 'axes4`. Set argument 's' to 80, 'c' to 'z' and 'marker' to '^'.
Add ticks on X-Axis at 0.0, 0.5, 1.0, 1.5 and ticks on Y-Axis at -0.2, 0.2, 0.6, 1.0 respectively
Adjust the entire layout with expression 'plt.tight_layout()'.
return the figure object

Task3

Create a function named generate_figure3.
Define a numpy array 'x' with expression 'np.arange(1, 301, 3)'.
Define another numpy array 'y1' with expression 'y1 = x'.
Define another numpy array 'y2' with expression 'y2 = x**2'.
Define another numpy array 'y3' with expression 'y3 = x**3'.
Create a figure of size 9 inches in width, and 7 inches in height. Name it as fig.
Define a grid 'gr' of 2 rows and 2 columns, using 'GridSpec' function. Ensure that 'matplotlib.gridspec' is imported, before defining the grid.
Create an axes, using plt.subplot function. Name it as axes1. The subplot must span the 1st row and 1st column of the defined grid 'gr'. Set 'title' argument to 'y = x'.
Draw a line plot of 'x' and 'y1' using 'plot' function on 'axes1`.
Create an axes, using plt.subplot function. Name it as axes2. The subplot must span 2nd row and 1st column of defined grid 'gr'. Set 'title' argument to 'y = x**2'.
Draw a line plot of 'x' and 'y2' using 'plot' function on 'axes2`.
Create an axes, using plt.subplot function. Name it as axes3. The subplot must span all rows of 2nd column of defined grid 'gr'. Set 'title' argument to 'y = x**3'.
Draw a line plot of 'x' and 'y3' using 'plot' function on 'axes3`.
Adjust the entire layout with the expression 'plt.tight_layout()'.
return the figure object

Note: The results of preliminary validation doesn't impact final scoring. In-depth scorings are done at a later stage.

Once you are in the Web IDE:

Open prog.py in the jupyter lab the file and start your coding by following the instructions given above.
Once you are done with the solution , then run the following commands in the terminal to check your solutions. Click File -> New -> Terminal, run the following commands
```
python3 prog.py
```
After running the test cases, click the submit button and click on Submit Test to end the assessment.

Note - Here Rough_Work.ipynb can be used for rough work to get the solutions

Solution

import numpy as np
import matplotlib.pyplot as plt


def generate_figure1():

    # Write your functionality below
    fig = plt.figure(figsize=(12, 7))
    x = np.arange(0.0, 10.0, 0.01)
    arr_s1 = np.sin(3 * np.pi * x)
    arr_s2 = np.sin(6 * np.pi * x)

    axes1 = plt.subplot(2,1,1,title="Sin(3*pi*x)")
    axes1.plot(x, arr_s1)

    axes2 = plt.subplot(2,1,2,title="Sin(6*pi*x)")
    axes2.plot(x, arr_s2)
    return fig


def generate_figure2():

    # Write your functionality below
    fig = plt.figure(figsize=(9, 7))
    np.random.seed(1500)
    x = np.random.rand(10)
    y = np.random.rand(10)
    z = np.sqrt(x**2 + y**2)

    axes1 = plt.subplot(2, 2, 1, title="Scatter plot with Diamond Markers")
    axes1.scatter(x, y, s=80, c=z, marker='d')
    axes1.set_xticks([0.0, 0.5, 1.0, 1.5])
    axes1.set_yticks([-0.2, 0.2, 0.6, 1.0])

    axes2 = plt.subplot(2, 2, 2, title="Scatter plot with Circle Markers")
    axes2.scatter(x, y, s=80, c=z, marker='o')
    axes2.set_xticks([0.0, 0.5, 1.0, 1.5])
    axes2.set_yticks([-0.2, 0.2, 0.6, 1.0])

    axes3 = plt.subplot(2, 2, 3, title="Scatter plot with Plus Markers")
    axes3.scatter(x, y, s=80, c=z, marker='+')
    axes3.set_xticks([0.0, 0.5, 1.0, 1.5])
    axes3.set_yticks([-0.2, 0.2, 0.6, 1.0])

    axes4 = plt.subplot(2, 2, 4, title="Scatter plot with Upper Triangle Markers")
    axes4.scatter(x, y, s=80, c=z, marker='^')
    axes4.set_xticks([0.0, 0.5, 1.0, 1.5])
    axes4.set_yticks([-0.2, 0.2, 0.6, 1.0])

    plt.tight_layout()
    return fig


def generate_figure3():
    import matplotlib.gridspec as gridspec
    # Write your functionality below
    x = np.arange(1, 301, 3)
    y1 = x
    y2 = x**2
    y3 = x**3

    fig = plt.figure(figsize=(9, 7))
    gr = gridspec.GridSpec(2,2)

    axes1 = plt.subplot(gr[0,0], title='y = x')
    axes1.plot(x, y1)

    axes2 = plt.subplot(gr[1,0], title="y = x**2")
    axes2.plot(x, y2)

    axes3 = plt.subplot(gr[:,1], title="y = x**3")
    axes3.plot(x, y3)

    plt.tight_layout()
    return fig


# Note: Do Not modify the below code
if __name__ == '__main__':
    import sys
    import subprocess
    subprocess.check_call(
        [sys.executable, "-m", "pip", "install", 'test_plot6-0.2-py3-none-any.whl'], stdout=subprocess.DEVNULL)
    from test_plot6 import matplotlib6
    usr_fig1 = generate_figure1()
    usr_fig2 = generate_figure2()
    usr_fig3 = generate_figure3()
    matplotlib6.save_answer(usr_fig1, usr_fig2, usr_fig3)