Pandas DataFrame: Select the specified columns and rows from a given DataFrame
Pandas: DataFrame Exercise-6 with Solution
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
Python-Pandas Code Editor:
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Previous: Write a Pandas program to select the 'name' and 'score' columns from the following DataFrame.
Next: Write a Pandas program to select the rows where the number of attempts in the examination is greater than 2.
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Python: Tips of the Day
Join Strings in an Iterable:
>>> words = ('Hello', 'Python', 'Programmers') >>> '!'.join(words) 'Hello!Python!Programmers' >>> words_dict = {0: 'zero', 1: 'one', 2: 'two', 3: 'three'} >>> '&'.join(words_dict.values()) 'zero&one&two&three'
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