w3resource

Pandas DataFrame: Append a new row 'k' to DataFrame with given values for each column

Pandas: DataFrame Exercise-15 with Solution

Write a Pandas program to append a new row 'k' to DataFrame with given values for each column. Now delete the new row and return the original 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']
Values for each column will be:
name : ‘Suresh’, score: 15.5, attempts: 1, qualify: ‘yes’, label: ‘k’

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("Original rows:")
print(df)
print("\nAppend a new row:")
df.loc['k'] = [1, 'Suresh', 'yes', 15.5]
print("Print all records after insert a new record:")
print(df)
print("\nDelete the new row and display the original  rows:")
df = df.drop('k')
print(df)

Sample Output:

Original rows:
   attempts       name qualify  score
a         1  Anastasia     yes   12.5
b         3       Dima      no    9.0
c         2  Katherine     yes   16.5
d         3      James      no    NaN
e         2      Emily      no    9.0
f         3    Michael     yes   20.0
g         1    Matthew     yes   14.5
h         1      Laura      no    NaN
i         2      Kevin      no    8.0
j         1      Jonas     yes   19.0

Append a new row:
Print all records after insert a new record:
   attempts       name qualify  score
a         1  Anastasia     yes   12.5
b         3       Dima      no    9.0
c         2  Katherine     yes   16.5
d         3      James      no    NaN
e         2      Emily      no    9.0
f         3    Michael     yes   20.0
g         1    Matthew     yes   14.5
h         1      Laura      no    NaN
i         2      Kevin      no    8.0
j         1      Jonas     yes   19.0
k         1     Suresh     yes   15.5

Delete the new row and display the original  rows:
   attempts       name qualify  score
a         1  Anastasia     yes   12.5
b         3       Dima      no    9.0
c         2  Katherine     yes   16.5
d         3      James      no    NaN
e         2      Emily      no    9.0
f         3    Michael     yes   20.0
g         1    Matthew     yes   14.5
h         1      Laura      no    NaN
i         2      Kevin      no    8.0
j         1      Jonas     yes   19.0 

Python Code Editor:


Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a Pandas program to calculate the mean score for each different student in data frame.
Next: Write a Pandas program to sort the data frame first by 'name' in descending order, then by 'score' in ascending order.

What is the difficulty level of this exercise?

Test your Python skills with w3resource's quiz



Python: Tips of the Day

Dictionary comprehension:

>>> m = {x: x ** 2 for x in range(5)}
>>> m
{0: 0, 1: 1, 2: 4, 3: 9, 4: 16}