-Write a Pandas program to find the index of the first occurrence of the smallest and largest value of a given series. nums = pd.Series((8, 30, 39, 12, 29, 8, 25, 16, 22, 32, 15, 37, 35, 39, 26, 6]) -Write a program that will check the series equal or not one by one. nums1 = pd. Series([1, 8, 7, 5, 6, 5, 3, 4, 7, 1]) -Write a Pandas program to select the 'name' and 'score' columns from the following DataFrame. -Write a Pandas program to select the rows where the number of attempts in the examination is greater than 2. -Write a Pandas program to select the rows where the score is missing, i.e. is NaN.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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-Write a Pandas program to find the index of the first occurrence of the smallest and largest
value of a given series.
nums = pd.Series([8, 30, 39, 12, 29, 8, 25, 16, 22, 32, 15, 37, 35, 39, 26, 6])
-Write a program that will check the series equal or not one by one.
nums1 = pd. Series([1, 8, 7, 5, 6, 5, 3, 4, 7, 1])
-Write a Pandas program to select the 'name' and 'score' columns from the following
DataFrame.
-Write a Pandas program to select the rows where the number of attempts in the examination is
greater than 2.
-Write a Pandas program to select the rows where the score is missing, i.e. is NaN.
exam_data = {'name': ['Ahmet', 'Mehmet", 'Zehra', 'Osman', 'Fatma', 'Mert', 'Cem', 'Kerem',
"Sevgi", 'Pınar],
'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
'qualify: ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', "b', 'c', 'd', 'e', 'f, 'g', 'h', 'r, '
Transcribed Image Text:-Write a Pandas program to find the index of the first occurrence of the smallest and largest value of a given series. nums = pd.Series([8, 30, 39, 12, 29, 8, 25, 16, 22, 32, 15, 37, 35, 39, 26, 6]) -Write a program that will check the series equal or not one by one. nums1 = pd. Series([1, 8, 7, 5, 6, 5, 3, 4, 7, 1]) -Write a Pandas program to select the 'name' and 'score' columns from the following DataFrame. -Write a Pandas program to select the rows where the number of attempts in the examination is greater than 2. -Write a Pandas program to select the rows where the score is missing, i.e. is NaN. exam_data = {'name': ['Ahmet', 'Mehmet", 'Zehra', 'Osman', 'Fatma', 'Mert', 'Cem', 'Kerem', "Sevgi", 'Pınar], 'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19], 'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1], 'qualify: ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']} labels = ['a', "b', 'c', 'd', 'e', 'f, 'g', 'h', 'r, '
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