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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

Sets Vs Lists Python Programmer Tips

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Sets are only useful when trying to ensure unique items are preserved. Before sets were available, it was common to process items and check if they exist in a list (or dictionary) before adding them. List example Here unique is an empty list. Every time I compare with this list, and if it is not duplicated then the input item will append to the unique list.  >>> unique = []  >>> for name in ['srini', 'srini', 'rao', 'srini']:  ... if name not in unique:  ... unique.append(name)  ... >>> unique ['srini', 'rao'] There is no need to do this when using sets. Instead of appending you add to a set: Set example >>> for name in ['srini', 'srini', 'rao', 'srini']: ... unique.add(name)  ...  >>> unique {'srini', 'rao'} Just like tuples and lists, interacting with sets have some differences on how to access their items. You can't index them like lists an