Pandas DataFrame: Select two specified columns from a given DataFrame
Pandas: DataFrame Exercise-5 with Solution
Write a Pandas program to select the 'name' and 'score' columns from the following DataFrame.
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:")
print(df[['name', 'score']])
Sample Output:
Select specific columns: name score a Anastasia 12.5 b Dima 9.0 c Katherine 16.5 d James NaN e Emily 9.0 f Michael 20.0 g Matthew 14.5 h Laura NaN i Kevin 8.0 j Jonas 19.0
Explanation:
The above code creates a Pandas DataFrame ‘df’ with columns 'name', 'score', 'attempts', and 'qualify' using a Python dictionary ‘exam_data’ and index ‘labels’.
df[['name', 'score']]: This line prints a subset of the DataFrame that includes only the 'name' and 'score' columns using the double square bracket notation .
Python-Pandas Code Editor:
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