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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
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How to Find Non-word Character: Python Regex Example

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In Python, the regular expression pattern \W matches any non-word character. Here's an example of usage. The valid word characters are [a-zA-Z0-9_]. \W (upper case W) matches any non-word character.



regex non-word character


Regex examples to find non-word char


#1 Example


import re
text = "Hello, world! How are you today?"
non_words = re.findall(r'\W', text)
print(non_words)


In the above example, the re.findall() function is used to find all non-word characters in the text string using the regular expression pattern \W. The output will be a list of non-word characters found in the string:


Output

[',', '!', ' ', ' ', '?']


This includes punctuation marks and spaces but excludes letters, digits, and underscores, which are considered word characters in regular expressions.


#2 Example


import re
text = "Hello, world! How are non-word-char:! you today?"
non_words = re.findall(r'non-word-char:\W', text)
print(non_words)


Output

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