PIAIC101064_𝐀𝐬𝐬𝐢𝐠𝐧𝐦𝐞𝐧𝐭𝟐.py

#!/usr/bin/env python
# coding: utf-8

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# Read Instructions carefully before attempting this assignment

# 1) don't rename any function name
# 2) don't rename any variable name
# 3) don't remove any #comment 
# 4) don't remove """ under triple quate values """
# 5) you have to write code where you found "write your code here"
# 6) after download rename this file with this format "PIAICCompletRollNumber_AssignmentNo.py"
#   Example piaic17896_Assignment1.py
# 7) After complete this assignment please push on your own GitHub repository.
# 8) you can submit this assignment through the google form
# 9) copy this file absolute URL then paste in the google form
#  The example above: https://github.com/EnggQasim/Batch04_to_35/blob/main/Sunday/1_30%20to%203_30/Assignments/assignment1.txt

# * Because all assignment we will be checked through software if you missed any above points 
# * then we can't assign your scores in our database.





import numpy as np


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# Task no 1
def function1():
    # create 2d array from 1,12 range 
    # dimension should be 6row 2 columns  
    # and assign this array values in x values in x variable
    # Hint: you can use arange and reshape numpy methods  
    x =  np.arange(1,13).reshape((6,2)) 

    return x
    """
    expected output:
    [[ 1  2]
    [ 3  4]
    [ 5  6]
    [ 7  8]
    [ 9 10]
    [11 12]]
    """


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function1()


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def function2():
    #create 3D array (3,3,3)
    #must data type should have float64
    #array value should be satart from 10 and end with 36 (both included)
    # Hint: dtype, reshape 
    
    x = np.arange(start=10, stop=37, step=1,dtype=np.float64).reshape(3,3,3)


    return x
    """
    Expected: out put
array([[[10., 11., 12.],
        [13., 14., 15.],
        [16., 17., 18.]],

       [[19., 20., 21.],
        [22., 23., 24.],
        [25., 26., 27.]],

       [[28., 29., 30.],
        [31., 32., 33.],
        [34., 35., 36.]]])    
    """


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function2()


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#task3
def function3():
    #extract those numbers from given array. those are must exist in 5,7 Table
    #example [35,70,105,..]
    a = np.arange(1, 100*10+1).reshape((100,10))
    x = a[a%35==0] #wrtie your code here
    return x
    """
    Expected Output:
     [35,  70, 105, 140, 175, 210, 245, 280, 315, 350, 385, 420, 455,
       490, 525, 560, 595, 630, 665, 700, 735, 770, 805, 840, 875, 910,
       945, 980] 
    """ 
 


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function3()


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def function4():
    #Swap columns 1 and 2 in the array arr.
   
    arr = np.arange(9).reshape(3,3)
    arr[:,[0, 1]] = arr[:,[1, 0]]
    return arr #wrtie your code here
    """
    Expected Output:
          array([[1, 0, 2],
                [4, 3, 5],
                [7, 6, 8]])
    """ 
 


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function4()


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#task5
def function5():
    #Create a null vector of size 20 with 4 rows and 5 columns with numpy function
    z = np.zeros(shape=(4,5), dtype=int)
  
    return z
    """
    Expected Output:
          array([[0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0],
                [0, 0, 0, 0, 0]])
    """ 


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function5()


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#task6
def function6():
    # Create a null vector of size 10 but the fifth and eighth value which is 10,20 respectively
   
    arr = (np.arange(10) == 4).astype(int)
    arr[7] = 1
  
    return arr
   


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function6()


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#task7
def function7():
#  Create an array of zeros with the same shape and type as X. Dont use reshape method
x = np.arange(4, dtype=np.int64)
n = x.shape
arr = np.zeros(shape=(n), dtype=int)
return arr

"""
Expected Output:
      array([0, 0, 0, 0], dtype=int64)
""" 


# In[72]:


function7()


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#task8
def function8():
    # Create a new array of 2x5 uints, filled with 6.

    x = np.full((2, 5), 6, dtype=int)
    return x

    """
    Expected Output:
          array([[6, 6, 6, 6, 6],
                 [6, 6, 6, 6, 6]], dtype=uint32)
    """ 


# In[82]:


function8()


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#task9
def function9():
    # Create an array of 2, 4, 6, 8, ..., 100.

    a = np.arange(1, 101)
    x = a[a%2==0] #wrtie your code here
    return x
    """
    Expected Output:
          array([  2,   4,   6,   8,  10,  12,  14,  16,  18,  20,  22,  24,  26,
                28,  30,  32,  34,  36,  38,  40,  42,  44,  46,  48,  50,  52,
                54,  56,  58,  60,  62,  64,  66,  68,  70,  72,  74,  76,  78,
                80,  82,  84,  86,  88,  90,  92,  94,  96,  98, 100])
    """ 


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function9()


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#task10
def function10():
    # Subtract the 1d array brr from the 2d array arr, such that each item of brr subtracts from respective row of arr.

    arr = np.array([[3,3,3],[4,4,4],[5,5,5]])
    brr = np.array([1,2,3])

    return arr - brr[:,None]

    """
    Expected Output:
           array([[2 2 2]
                  [2 2 2]
                  [2 2 2]])
    """ 


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function10()


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#task11
def function11():
    # Replace all odd numbers in arr with -1 without changing arr.

    arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
    ans = arr.copy()
    ans = np.where(ans % 2 == 1,-1, ans)

    return ans

    """
    Expected Output:
          array([ 0, -1,  2, -1,  4, -1,  6, -1,  8, -1])
    """ 


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function11()


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#task12
def function12():
    # Create the following pattern without hardcoding. Use only numpy functions and the below input array arr.
    # HINT: use stacking concept

    arr = np.array([1,2,3])
    ans1 = np.repeat(arr, 3)
    ans2 = np.hstack((arr,arr,arr))
    ans = np.concatenate([ans1,ans2])
    #ans = np.hstack((arr,arr,arr))

    return ans

    """
    Expected Output:
          array([1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3])
    """ 


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function12()


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#task13
def function13():
    # Set a condition which gets all items between 5 and 10 from arr.


    arr = np.array([2, 6, 1, 9, 10, 3, 27])
    ans = arr[arr > 5]
    ans = ans[ans < 10]

    return ans

    """
    Expected Output:
          array([6, 9])
    """ 


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function13()


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#task14
def function14():
    # Create an 8X3 integer array from a range between 10 to 34 such that the difference between each element is 1 and then Split the array into four equal-sized sub-arrays.
    # Hint use split method


    arr = np.arange(10, 34, 1) #write reshape code
    ans = arr.reshape(8,3)
    ans = np.array_split(ans, 4)

    return ans

    """
    Expected Output:
    [array([[10, 11, 12],[13, 14, 15]]), 
    array([[16, 17, 18],[19, 20, 21]]), 
    array([[22, 23, 24],[25, 26, 27]]), 
    array([[28, 29, 30],[31, 32, 33]])]
    """ 


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function14()


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#task15
def function15():
    #Sort following NumPy array by the second column


    arr = np.array([[ 8,  2, -2],[-4,  1,  7],[ 6,  3,  9]])
    ans = arr[arr[:,1].argsort(kind='mergesort')]


    return ans

    """
    Expected Output:
       array([[-4,  1,  7],
               [ 8,  2, -2],
               [ 6,  3,  9]])
    """ 


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function15()


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#task16
def function16():
    #Write a NumPy program to join a sequence of arrays along depth.


    x = np.array([[1], [2], [3]])
    y = np.array([[2], [3], [4]])
    ans = np.dstack((x,y))

    return ans

    """
    Expected Output:
            [[[1 2]]

             [[2 3]]

             [[3 4]]]
    """ 


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function16()


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#Task17
def function17():
    # replace numbers with "YES" if it divided by 3 and 5
    # otherwise it will be replaced with "NO"
    # Hint: np.where
    arr = np.arange(1,10*10+1).reshape((10,10))
    #arr = np.where((arr%3==1) & (arr%3==1), 'NO', arr )
    #return np.where((arr%3==0) & (arr%5==0), 'YES', arr) # Write Your Code HERE
   # return np.where((arr%3==0) & (arr%5==0), 'YES', np.where((arr%3==1) & (arr%3==1), 'NO', np.where((arr%3==0) | (arr%11==0), 'NO', np.where((arr%2==0) | (arr%5==0), 'NO', arr ) ) )) # Write Your Code HERE
    return     np.where((arr%3==0) & (arr%5==0), 'YES', np.where((arr) , 'NO',arr) ) # Write Your Code HERE

#    return np.where((arr%3==0) & (arr%5==0), 'YES', arr) 

    #   (np.where((arr%3==1) & (arr%3==1), 'NO',arr)
    #Excpected Out
    """
    array([['NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO'],
           ['NO', 'NO', 'NO', 'NO', 'YES', 'NO', 'NO', 'NO', 'NO', 'NO'],
           ['NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'YES'],
           ['NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO'],
           ['NO', 'NO', 'NO', 'NO', 'YES', 'NO', 'NO', 'NO', 'NO', 'NO'],
           ['NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'YES'],
           ['NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO'],
           ['NO', 'NO', 'NO', 'NO', 'YES', 'NO', 'NO', 'NO', 'NO', 'NO'],
           ['NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'YES'],
           ['NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO']],
          dtype='<U3')
    """


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function17()


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#Task18
def function18():
    # count values of "students" are exist in "piaic"
    piaic = np.arange(100)
    students = np.array([5,20,50,200,301,7001])
    x = np.intersect1d(piaic,students)    
    return len(x)

    #Expected output: 3


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function18()


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def function19():
    #Create variable "X" from 1,25 (both are included) range values
    #Convert "X" variable dimension into 5 rows and 5 columns
    #Create one more variable "W" copy of "X" 
    #Swap "W" row and column axis (like transpose)
    # then create variable "b" with value equal to 5
    # Now return output as "(X*W)+b:

    X =  np.arange(1,26).reshape(5,5) 
    W =  np.transpose(X.copy())
    b =  5
   # output =    # Write your code here
    return (X*W)+b
    #expected output
    """
    array([[  6,  17,  38,  69, 110],
       [ 17,  54, 101, 158, 225],
       [ 38, 101, 174, 257, 350],
       [ 69, 158, 257, 366, 485],
       [110, 225, 350, 485, 630]])
    """


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function19()


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def function20():
    #apply fuction "abc" on each value of Array "X"
    x = np.arange(1,11)
    def abc(x):
        return x*2+3-2

    return abc(x)
#Expected Output: array([ 3,  5,  7,  9, 11, 13, 15, 17, 19, 21])


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function20()


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