Assignment 2.py

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

# In[ ]:


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

# In[ ]:


# %load "Assignment2_NumpyBasicsToAdvance.py"
# 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.


# In[4]:


import numpy as np

# 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]]
    """


# In[7]:


# Task2
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(1,28,dtype=np.float64).reshape((3,3,3))     #wrtie your code here
    
    x=np.arange(10,37,dtype=np.float64).reshape(3,3,3)
    return x
    function2()
    """
    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.]]])    
    """


# In[8]:


function2()


# In[181]:


#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 % 5== 0) & (a %7 == 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]
    """ 


# In[182]:


function3()


# In[11]:


#task4
def function4():
    #Swap columns 1 and 2 in the array arr.
   
    arr = np.arange(9).reshape(3,3)
    x = arr[:,[0, 1, 2]] = arr[:,[1, 0, 2]]
    return x #wrtie your code here

    """
    Expected Output:
          array([[1, 0, 2],
                [4, 3, 5],
                [7, 6, 8]])
    """ 
   


# In[12]:


function4()


# In[14]:



#task5
def function5():
   #Create a null vector of size 20 with 4 rows and 5 columns with numpy function
  
   z = np.zeros((4,5)) #wrtie your code here
 
   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]])
   """ 


# In[15]:


function5()


# In[59]:


#task6
def function6():
    # Create a null vector of size 10 but the fifth and eighth value which is 10,20 respectively
   
    arr = np.zeros(10) #wrtie your code here
    arr[5] = 10
    return arr
   
  


# In[60]:


function6()


# In[79]:



#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)
  y = np.zeros(4,dtype=np.int64)
  return y #write your code here

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


# In[80]:


function7()


# In[19]:


#task8
def function8():
    # Create a new array of 2x5 uints, filled with 6.
    
    x=np.arange(10).reshape(2,5) #write your code here
    x[:]=6 
    return x
    """
     Expected Output:
              array([[6, 6, 6, 6, 6],
                     [6, 6, 6, 6, 6]], dtype=uint32)
    """ 
  


# In[20]:


function8()


# In[23]:


#task9
def function9():
    # Create an array of 2, 4, 6, 8, ..., 100.
    
    a = np.arange(2,102,2) # write your code here
  
    return a

    """
     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])
     """ 
    


# In[24]:


function9()


# In[86]:


#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])
    subt = arr - np.vstack(brr)  # write your code here 
  
    return subt

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


# In[87]:


function10()


# In[147]:


#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])
    arr[1::2]= -1 #write your code here 
    ans = arr
    return ans

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


# In[148]:


function11()


# In[ ]:


#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])
    ans = #write your code here 
  
    return ans

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


# In[ ]:





# In[157]:


#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) & (arr<10)] #write your code here 
  
    return ans

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


# In[158]:


function13()


# In[162]:


#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).reshape(8,3) #write reshape code
    ans = np.array_split(arr,4) #write your code here 
  
    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]])]
     """ 
   


# In[163]:


function14()


# In[5]:


#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[[0, 1, 2],:] = arr[[1, 0, 2],:] #write your code here 
  
    return ans

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


# In[6]:


function15()


# In[164]:



#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)) #write your code here 

  return ans

  """
   Expected Output:
              [[[1 2]]
               [[2 3]]
               [[3 4]]]
   """ 
  


# In[165]:


function16()


# In[171]:



#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))
y = np.where((arr%3==0) & (arr%5==0),'YES','NO')
return y         # Write Your Code HERE

#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')
"""


# In[172]:


function17()


# In[179]:


#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.size([np.where(students<100)]) # Write you code Here
    return x

    #Expected output: 3


# In[180]:


function18()


# In[51]:


# Task19
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)  # Write your code here
    W = np.transpose(X)  # Write your code here 
    b = 5  # Write your code here
    output = (X * W)+b  # Write your code here
    return output
    #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]])
    """


# In[52]:


function19()


# In[66]:


#Task20
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 x*2+3-2 #Write your Code here
#Expected Output: array([ 3,  5,  7,  9, 11, 13, 15, 17, 19, 21])
#--------------------------X-----------------------------X-----------------------------X----------------------------X---------------------


# In[67]:


function20()