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5.  Consider the following two series storing marks and subjects of two different students with roll numbers: 101 and 102:
                 marks:
                 101    95
                 101    89
                 101    92
                 102    95
                 102    90
                 102    75
                 dtype: int64
                 subjects:
                 101         Math
                 101      Physics
                 101    Chemistry
                 102         Math
                 102    Chemistry
                 102      Physics
                 dtype: object
                  Write the code snippet for the following queries based on above mentioned series:
                  (i)  Find the highest and lowest marks.
                  (ii)  Determine the subject name(s) with the highest marks obtained in previous part.
                  (iii)  Determine the average marks scored in Math.
                  (iv)  Find the number of subjects in which the student scored above 90.
                  (v)  Find the subjects in which the student scored below 90.
                  (vi)  Find the average marks scored by student with roll number 101.


                  Case-based Questions


                  Suppose the teacher-in charge of class XII wishes to determine top 5 scorers in the Arts subject. She has access to the
                  following Pandas Series representing the scores of ten students in arts subjects :
                  artScores = pd.Series([85, 92, 78, 89, 95, 87, 93, 91, 84, 88])
                  Help the teacher-in charge by writing a Python code snippet to extract the scores of the top 5 students using indexing and
                  slicing.


                                           Previous Years' Questions


               1.  Write a Python program to create a series object, country using a list that stores the capital of each country.   [2023]
                  Assume four countries to be used as index of the series object are India, UK, Denmark, and Thailand having their capitals
                  as New Delhi, London, Copenhagen, and Bangkok respectively.
             Ans.  import pandas as pd
                  l=['New Delhi', 'London', 'Copenhagen','Bangkok']
                  country=pd.Series(['New Delhi', 'London', 'Copenhagen','Bangkok'],
                      index=['India', 'UK', 'Denmark','Thailand'])
                  print(country)






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