Featured Post

14 Top Data Pipeline Key Terms Explained

Image
 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...

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
        else:
            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
print(most_common_brute_force(list_1))
print(most_common_brute_force(list_2))

Output

2
   

Comments

Popular posts from this blog

How to Fix datetime Import Error in Python Quickly

SQL Query: 3 Methods for Calculating Cumulative SUM

Big Data: Top Cloud Computing Interview Questions (1 of 4)