Featured Post

The Quick and Easy Way to Analyze Numpy Arrays

The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par

Here's Python Program for List Duplicates

Here is a program to find the item that occurs most frequently in a data structure. So why to find frequent item? Maybe it is the most purchased item on your shopping site. Perhaps it is the web page that gets hit the most often.

If you are a tester, it could easily be the test that has had the most failures over the last year. Whatever it is, you want an easy way to find the data you need, and Python is here to help you.

Python List duplicates

List frequent item

Here are the two simple lists:

list_1 = [1,2,3,2,3,2] 
list_2 = ['a', 'b', 'a', 'b', 'c']

  • We can't do simple math on the individual items since the second list contains characters. For example, it could contain the words of a book, and you want to find the most commonly used word in the work. 
  • Also, it maybe list of UPC values for commonly purchased items. Whatever it is, all we can guarantee is that the data is probably comparable, in that we can compare one of the items to another. Yet we need to find frequent items.

Python program

Below, you will find a program to find repeated values.

list_1 = [1,2,3,2,3,2]
list_2 = ['a', 'b', 'a', 'b', 'c']

def most_common_brute_force(l):

  # Find the counts of all elements
    dict_of_counts = {}
    for i in l:
        if i in dict_of_counts.keys():
            dict_of_counts[i] = dict_of_counts[i] + 1
            dict_of_counts[i] = 1

            max_count = -1
            max_value = -1
        for k, v in dict_of_counts.items():
            if v > max_count:
                max_count = v
                max_value = k
    return max_value




Popular posts from this blog

How to Decode TLV Quickly

7 AWS Interview Questions asked in Infosys, TCS