Pandas DataFrame: Select the specified columns and rows from a given DataFrame

Last update on December 21 2024 07:42:16 (UTC/GMT +8 hours)

Write a Pandas program to select the specified columns and rows from a given DataFrame.
Select 'name' and 'score' columns in rows 1, 3, 5, 6 from the following data frame.

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("Select specific columns and rows:")
print(df.iloc[[1, 3, 5, 6], [1, 3]])

Sample Output:

Select specific columns and rows:
   score qualify
b    9.0      no
d    NaN      no
f   20.0     yes
g   14.5     yes                               

Explanation:

The above code creates a Pandas DataFrame named 'df' containing information related to students' 'exam_data'

print(df.iloc[[1, 3, 5, 6], [1, 3]]):

• In the said code iloc() function is used to select specific rows and columns from the DataFrame based on their integer location.
• [[1, 3, 5, 6], [1, 3]] is used as the parameter to select the rows with index 1, 3, 5, and 6 and columns with index 1 and 3 from the DataFrame.
• The selected rows contain the information for the students with the index label b, d, f, and g.
• The selected columns contain the information for the columns ‘score’ and ‘qualify’.
• Finally print() function prints 4 rows and 2 columns.

Python-Pandas Code Editor:

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