<prompt> Ha u fuoa dataset, fumana khokahano lipakeng tsa mefuta e meli.Lethathamo la lintlha  <response>: Instruction in English: Given a dataset, find the correlation between two variables. . Response in English: To find the correlation between two variables in the given dataset, we need to follow a few steps:1. First, we need to make sure that the two variables we want to find the correlation between are numerical. If they are not, we need to convert them to numerical values.2. Next, well import a statistical library such as Pandas or Numpy to compute the correlation. 3. Then, well extract the two columns with the desired variables from the dataset and save them into two separate variables.4. After that, well use the .corr function to compute the correlation between the two variables. We may specify the method we want to use to calculate the correlation Pearson, Kendall, or Spearman. If no method is specified, the default is Pearson. 5. Finally, well interpret the result. A value of 1 indicates a strong positive correlation, while a value of -1 indicates a strong negative correlation. A value of 0 indicates no correlation.Here is an example code in Python using the Pandas library to compute the correlation between two variables X and Y from a given dataset:pythonimport pandas as pddata pd.read_csvdataset.csv load datasetX dataX extract first variable columnY dataY extract the second variable columncorrelation X.corrY, method pearson compute correlationprintThe correlation between X and Y is: , correlationThis code will output the correlation between the two specified variables from the given dataset. . Response in Sesotho: Ho fumana kamano pakeng tsa mefuta e meli ea dataset e fanoeng, re lokela ho latela mehato e seng mekae: 1. Pele, re lokela ho etsa bonnete ba hore mefuta e meli eo re batlang ho fumana kamano pakeng tsa eona ke linomoro. Haeba ha li joalo, re hloka ho li fetolela ho litekanyetso tsa linomoro. 2. E latelang, re tla tlisa laeborari ea lipalo-palo joalo ka Pandas kapa Numpy ho kopanya khokahano. 3. Joale, re tla ntša litšiea tse peli ka mefuta e lakatsehang ho tswa ho dataset ebe re li boloka ka mefuta e meli e fapaneng. 4. Ka mora moo, re tla sebelisa .corr mosebetsi ho bala kamano pakeng tsa mefuta e meli. Re ka hlakisa mokhoa oo re batlang ho o sebelisa ho bala khokahano Pearson, Kendall, kapa Spearman. Haeba ho se mokhoa o boletsoeng, oa kamehla ke Pearson. 5. Qetellong, re tla toloka sephetho. Boleng ba 1 bo bontša kamano e matla e ntle, ha boleng ba -1 bo bontša kamano e matla e mpe. Boleng ba 0 bo bontša hore ha ho na kamano. Mona ke mohlala oa khoutu ho Python o sebelisang laeborari ea Pandas ho kopanya khokahano lipakeng tsa mefuta e meli ea X le Y ho tsoa ho dataset e fanoeng: python import pandas as pd data pd.read_csvdataset.csv mojaro dataset X dataX ho ntša kholomo e feto-fetohang ea pele Y dataY ho ntša kholumo ea bobeli e feto-fetohang correlation X.corrY, mokhoa pearson compute correlation print Kamano pakeng tsa X le Y ke: , kamano Khoutu ena e tla hlahisa kamano pakeng tsa mefuta e meli e boletsoeng ho tsoa ho dataset e fanoeng. 