{"id":138436,"date":"2026-02-18T16:10:50","date_gmt":"2026-02-18T10:40:50","guid":{"rendered":"https:\/\/www.vskills.in\/certification\/tutorial\/?page_id=138436"},"modified":"2026-02-20T09:09:40","modified_gmt":"2026-02-20T03:39:40","slug":"logical-operators-2","status":"publish","type":"page","link":"https:\/\/www.vskills.in\/certification\/tutorial\/logical-operators-2\/","title":{"rendered":"Logical Operators"},"content":{"rendered":"\n

Logical operators in Python are used to combine conditions and make decisions more accurately. They return True or False, and they are most commonly used in conditional statements, filtering rules, and validation checks. In data analysis, logical operators help you build business logic such as selecting records that meet multiple criteria, excluding unwanted cases, or defining rules for categorisation.<\/p>\n\n\n\n

Python has three main logical operators: and, or, and not.<\/p>\n\n\n\n

The and operator returns True only when all conditions are true. If even one condition is false, the result becomes false. This is useful when you need multiple requirements at the same time. For example, you may want records where region is \u201cNorth\u201d and sales are greater than 10,000.<\/p>\n\n\n\n

The or operator returns True if at least one condition is true. It becomes false only when all conditions are false. This is useful when you want to include multiple acceptable cases. For example, you may want records where category is \u201cElectronics\u201d or category is \u201cAppliances\u201d.<\/p>\n\n\n\n

The not operator reverses a condition. If the condition is true, not makes it false, and if the condition is false, not makes it true. This is useful when you want to exclude cases or check for absence. For example, you may want values that are not equal to \u201cCancelled\u201d or records that do not contain missing values.<\/p>\n\n\n\n

Logical operators are often used with comparison operators such as ==, !=, >, and <. Parentheses are important when you combine multiple conditions, because they make your logic clear and prevent mistakes. Understanding these operators helps you write correct filters and rules, which is a core part of data cleaning and analysis.<\/p>\n\n\n\n

\"\"<\/a><\/figure>\n","protected":false},"excerpt":{"rendered":"

Logical operators in Python are used to combine conditions and make decisions more accurately. They return True or False, and they are most commonly used in conditional statements, filtering rules, and validation checks. In data analysis, logical operators help you build business logic such as selecting records that meet multiple criteria, excluding unwanted cases, or…<\/p>\n","protected":false},"author":21,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-138436","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nLogical Operators - Tutorial<\/title>\n<meta name=\"description\" content=\"Logical operators in Python are used to combine conditions and make decisions more accurately. 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