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SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries

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 Here are the five top commonly asked SQL queries in the interviews. These you can expect in Data Analyst, or, Data Engineer interviews. Top SQL Queries for Interviews 01. Joins The commonly asked question pertains to providing two tables, determining the number of rows that will return on various join types, and the resultant. Table1 -------- id ---- 1 1 2 3 Table2 -------- id ---- 1 3 1 NULL Output ------- Inner join --------------- 5 rows will return The result will be: =============== 1  1 1   1 1   1 1    1 3    3 02. Substring and Concat Here, we need to write an SQL query to make the upper case of the first letter and the small case of the remaining letter. Table1 ------ ename ===== raJu venKat kRIshna Solution: ========== SELECT CONCAT(UPPER(SUBSTRING(name, 1, 1)), LOWER(SUBSTRING(name, 2))) AS capitalized_name FROM Table1; 03. Case statement SQL Query ========= SELECT Code1, Code2,      CASE         WHEN Code1 = 'A' AND Code2 = 'AA' THEN "A" | "A

Text Vs. Binary Vs. UTF-8 Top differences

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Here are the differences between Text files, Binary files, and UTF-8. These would help understanding files correctly for beginners. Text File It contains plain text characters. When you open a text file in a text editor, it displays human-readable content.  The text may not be in a language you know or understand, but you will see mostly normal characters that you can type at any keyboard. Binary File It stores information in bytes that aren’t quite so human readable.  If you open the binary file in a text editor, it will not be readable. UTF-8 UTF-8 is short for Unicode Transformation Format, 8-bit, and is a standardized way to represent letters and numbers on computers. The original ASCII set of characters, which contains mostly uppercase and lowercase letters, numbers, and punctuation marks, worked okay in the early days of computing. But when other languages were brought into the mix, these characters were just not enough. Many standards for dealing with other languages have been p

Python Web data - How to Extract HTML Tags Easily

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With BeautifulSoup you can extract HTML and XML tags easily that present in Web data. Here is the best example of how to remove these. The prime step of text analytics is cleaning . You can remove HTML tags using BeautifulSoup parser. Check out Python Logic and removing HTML tags. When analyzing web data, consider the below examples for your projects. Python Ideas to Remove HTML tags How I Removed Using BeautifulSoup Import BeautifulSoup Python Logic to Remove HTML tags Before and after executing the code 1. Import BeautifulSoup import  BeautifulSoup  from  bs4 2. Python BeautifulSoup: How to Remove HTML Tags from  bs4  import  BeautifulSoup soup =  BeautifulSoup ("<!DOCTYPE html><html><body><h1>My First Heading</h1><p>My first paragraph.</p></body></html>") text = soup. get_text() print (text) 3. Before and After Run Before the run see the below code. Before Executing the code After Run the tags are parsed. The means in