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Pandas DataFrame: Select the rows where the number of attempts in the examination is greater than 2

Pandas: DataFrame Exercise-7 with Solution

Write a Pandas program to select the rows where the number of attempts in the examination is greater than 2.

Sample DataFrame:
exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
'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', 'i', 'j']

Sample Solution :

Python Code :

import pandas as pd
import numpy as np

exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        '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', 'i', 'j']

df = pd.DataFrame(exam_data , index=labels)
print("Number of attempts in the examination is greater than 2:")
print(df[df['attempts'] > 2])

Sample Output:

Number of attempts in the examination is greater than 2:
      name  score  attempts qualify
b     Dima    9.0         3      no
d    James    NaN         3      no
f  Michael   20.0         3     yes

Explanation:

The above code creates a DataFrame 'df' containing information about a group of students who took an exam. The code then filters the DataFrame to only include rows where the 'attempts' column has a value greater than 2 using the boolean indexing method.

Finally, print() function prints the filtered DataFrame.

Python-Pandas Code Editor:

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Previous: Write a Pandas program to select the specified columns and rows from a given DataFrame.
Next: Write a Pandas program to count the number of rows and columns of a DataFrame.

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Python: Tips of the Day

Maps the values of a list to a dictionary using a function, where the key-value pairs consist of the original value as the key and the result of the function as the value:

Example:

def tips_map_dictionary(itr, fn):
  ret = {}
  for a in itr:
    ret[a] = fn(a)
  return ret
print(tips_map_dictionary([2,4,6], lambda a: a * a))

Output:

{2: 4, 4: 16, 6: 36}

 

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