{"media":{"type":{"params":{"contentName":"Image"},"library":"H5P.Image 1.1","subContentId":"40f707fe-009b-42e0-ba29-013a3c180337","metadata":{"contentType":"Image","license":"U","title":"Untitled Image"}},"disableImageZooming":false},"answers":[{"correct":false,"tipsAndFeedback":{"tip":"","chosenFeedback":"","notChosenFeedback":""},"text":"

final.pivot_table(values = 'League', index = 'Points', aggfunc = 'sum')<\/div>\n"},{"correct":true,"tipsAndFeedback":{"chosenFeedback":"When you use the \u2018pivot_table\u2019 to group your dataframe, you need to set the index to the column for which you want to group (in this case, \u2018League\u2019), \u2018values\u2019 to the column on which you need to perform any function (in this case, \u2018Points\u2019) and \u2018aggfunc\u2019 to the function which you need to perform (in this case, \u2018sum\u2019).\n\nWhen you use \u2018groupby\u2019 to group your dataframe, you need to provide the column by which you want to group the dataframe as an argument to groupby (in this case, \u2018League\u2019). When you perform this groupby, you get a dataframe and thus, can access any column in the dataframe by using square brackets as usual. And then, you perform the sum() operation on this dataframe to find the sum of the \u2018Points\u2019 for different leagues.\n","tip":"","notChosenFeedback":""},"text":"

final.pivot_table(values = 'Points', index = 'League', aggfunc = 'sum')<\/div>\n"},{"correct":true,"tipsAndFeedback":{"tip":"","chosenFeedback":"","notChosenFeedback":""},"text":"

final.groupby('League')['Points'].sum()<\/div>\n"},{"correct":false,"tipsAndFeedback":{"tip":"","chosenFeedback":"","notChosenFeedback":""},"text":"

final.groupby('Points')['League'].sum()<\/div>\n"}],"overallFeedback":[{"from":0,"to":100}],"behaviour":{"enableRetry":true,"enableSolutionsButton":true,"enableCheckButton":true,"type":"auto","singlePoint":false,"randomAnswers":true,"showSolutionsRequiresInput":true,"confirmCheckDialog":false,"confirmRetryDialog":false,"autoCheck":false,"passPercentage":100,"showScorePoints":true},"UI":{"checkAnswerButton":"Check","showSolutionButton":"Show solution","tryAgainButton":"Retry","tipsLabel":"Show tip","scoreBarLabel":"You got :num out of :total points","tipAvailable":"Tip available","feedbackAvailable":"Feedback available","readFeedback":"Read feedback","wrongAnswer":"Wrong answer","correctAnswer":"Correct answer","shouldCheck":"Should have been checked","shouldNotCheck":"Should not have been checked","noInput":"Please answer before viewing the solution","a11yCheck":"Check the answers. The responses will be marked as correct, incorrect, or unanswered.","a11yShowSolution":"Show the solution. The task will be marked with its correct solution.","a11yRetry":"Retry the task. Reset all responses and start the task over again."},"confirmCheck":{"header":"Finish ?","body":"Are you sure you wish to finish ?","cancelLabel":"Cancel","confirmLabel":"Finish"},"confirmRetry":{"header":"Retry ?","body":"Are you sure you wish to retry ?","cancelLabel":"Cancel","confirmLabel":"Confirm"},"question":"

Which command will achieve this?<\/p>\n"}

Look at the dataframe named ‘final’; given below and answer the questions that follow:

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