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

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## Python: Tips of the Day

Inserting if statements using conditional list comprehensions:

```x = [1, 2, 3, 4, 5, 6]
result = []
for idx in range(len(x)):
if x[idx] % 2 == 0:
result.append(x[idx] * 2)
else:
result.append(x[idx])
result
```

Output:

```[1, 4, 3, 8, 5, 12]
```
`[(element * 2 if element % 2 == 0 else element) for element in x]`

Output:

```[1, 4, 3, 8, 5, 12]
```
`[element * 2 for element in x if element % 2 == 0]`

Output:

```[4, 8, 12]
```