Answer:
see explaination
Step-by-step explanation:
import random
import statistics
import sys
arr=[];
#initializing array of size 1001 with random integers from 1000 to 1500
for i in range(1001):
arr=arr+[random.randrange(1000,1500)]
#printing mean,max,min,standard dev,variance using statistics library
#please giv a like
print("Mean is : ", statistics.mean(arr))
print("max is : ",max(arr))
print("min is : ",min(arr))
print("Standard Deviation is % s " %(statistics.stdev(arr)));
print("Variance of the is % s " %(statistics.variance(arr)))
#Sorting the array using selection sort
for i in range(len(arr)):
min_idx = i
for j in range(i+1, len(arr)):
if arr[min_idx] > arr[j]:
min_idx = j
arr[i], arr[min_idx] = arr[min_idx], arr[i]
#finding median using statistics
medianvalue=statistics.median(arr)
print("Median is : % s "% (medianvalue))
#Finding the index of median using linear search
print("The median value is found at using linear search is : ")
for i in range(len(arr)):
if arr[i] == medianvalue:
print(i)
#Finding the index of median using binary search
def binarySearch (arr, l, r, x):
# Check base case
if r >= l:
mid = l + (r - l)//2
# If element is present at the middle itself
if arr[mid] == x:
return mid
# If element is smaller than mid, then it can only
# be present in left subarray
elif arr[mid] > x:
return binarySearch(arr, l, mid-1, x)
# Else the element can only be present in right subarray
else:
return binarySearch(arr, mid+1, r, x)
else:
# Element is not present in the array
return -1
res=binarySearch(arr, 0, len(arr)-1,medianvalue )
print("The median value is found at using binary search is : ",res)
see attac