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Python --- Look at screenshot(s) --- Must have correct answer from (*** https://www.prairielearn.org/pl/course_instance/128819/instance_question/163662273/ ***) --- BEFORE YOU START: You need to pass Exercise 6.2 before
Python
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Look at screenshot(s)
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Must have correct answer from (*** https://www.prairielearn.org/pl/course_instance/128819/instance_question/163662273/ ***)
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BEFORE YOU START: You need to pass Exercise 6.2 before you can answer this question. A new dataset that we will be working with for the rest of the semester is the Heart Disease Data Set provided by UCI Machine Learning Repository. In this exercise, we will work with a small subset of this dataset, that is the processed Cleveland dataset. You can download this dataset here. The dataset description is provided in the Attribute Information on this site. The list includes 14 attributes that are included in the processed version of the Cleveland dataset. The complete attribute list includes all attributes in the raw version (which we are NOT working with today). Import this text file to a DataFrame called cleveland like you did in Ex 6.2 - Find all the rows with at Ieast1 missing value and store them in a DataFrame called missing_data. Note: The p rocessed.c1eve1and . data file is already loaded into your workspace on PrairieLearn. Simply use the path 'processed . Cleveland. data ' to load the dataset to Python. Your code snippet should define the following variables: Name Type Description missing_data DataFrame All rows with at least 1 missing value user_code.py 1 limit! Screenshot .lr'eStep by Step Solution
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