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If data is a Series, then data['a'] returns all values with the index value of a. However, if data is a DataFrame, then data['a'] returns all values in the column(s) named a. To avoid this ambiguity, Pandas supports the syntax data.loc['a'] as an alternative way to filter using the index.
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]
Deleting all rows from a table can be very time-consuming. Some DBMS [clarification needed] offer a TRUNCATE TABLE command that works a lot quicker, as it only alters metadata and typically does not spend time enforcing constraints or firing triggers. DELETE only deletes the rows. For deleting a table entirely the DROP command can be used.