<prompt> Bolela mekhoa e meraro ea ho hloekisa data.nan  <response>: Instruction in English: Name three techniques of data cleaning. . Response in English: 1. Removing duplicates: Duplication in a dataset can arise due to various reasons such as data entry errors or merging of datasets. Duplicate records can be identified using various methods such as record linkage and exact matching, and then removed from the dataset.2. Handling missing data: Missing data can be tackled using various techniques such as data imputation, where missing values are filled in based on other available data. Records with missing values can also be ignored or removed.3. Data transformation: Data transformation involves converting the data into a suitable form for analysis. This may involve normalizing or scaling the data, converting data types, or encoding categorical variables. The use of appropriate data transformation techniques can improve the quality of the data and make it easier to work with. . Response in Sesotho: 1. Ho tlosa likopi: Ho pheta-pheta ho dataset ho ka hlaha ka lebaka la mabaka a fapaneng joalo ka liphoso tsa ho kenya data kapa ho kopanngoa ha li-dataset. Lirekoto tse kopitsoang li ka bonoa ho sebelisoa mekhoa e fapaneng joalo ka khokahano ea rekoto le ho bapisa hantle, ebe li tlosoa pokellong ea data. 2. Ho sebetsana le lintlha tse sieo: Lintlha tse sieo li ka sebetsanoa ka mekhoa e sa tšoaneng e kang ho kenngoa ha data, moo litekanyetso tse sieo li tlatsitsoeng ho latela lintlha tse ling tse fumanehang. Lirekoto tse nang le litekanyetso tse sieo le tsona li ka hlokomolohuoa kapa tsa tlosoa. 3. Phetoho ea data: Phetoho ea data e kenyelletsa ho fetolela data hore e be foromo e loketseng bakeng sa tlhahlobo. Sena se ka kenyelletsa ho tloaeleha kapa ho lekanya datha, ho fetolela mefuta ea data, kapa ho kenyelletsa mefuta e fapaneng ea likarolo. Tšebeliso ea mekhoa e nepahetseng ea ho fetola data e ka ntlafatsa boleng ba data le ho etsa hore ho be bonolo ho sebetsa le eona. 