{"id":45426,"date":"2024-04-15T21:57:51","date_gmt":"2024-04-15T21:57:51","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=45426"},"modified":"2024-04-15T21:57:51","modified_gmt":"2024-04-15T21:57:51","slug":"which-of-the-following-operation-works-with-the-same-syntax-as-the-analogous-dict-operations","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/which-of-the-following-operation-works-with-the-same-syntax-as-the-analogous-dict-operations\/","title":{"rendered":"Which of the following operation works with the same syntax as the analogous dict operations?"},"content":{"rendered":"

[amp_mcq option1=”Getting columns” option2=”Setting columns” option3=”Deleting columns” option4=”All of the mentioned” correct=”option4″]<\/p>\n

The correct answer is: D. All of the mentioned<\/strong><\/p>\n

Pandas DataFrame columns can be accessed, set, and deleted using the same syntax as the analogous dict operations. For example, to access the value of a column, you can use the []<\/code> operator, just like you would with a dict. To set the value of a column, you can use the []=<\/code> operator. And to delete a column, you can use the del<\/code> keyword.<\/p>\n

Here are some examples:<\/p>\n

“`python<\/p>\n

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