How to append a list as a row to a Pandas DataFrame in Python?

To append a list as a row to a Pandas DataFrame in Python, we can use the concat() method (recommended) or the loc[] indexer. Let's first import the required library ?

import pandas as pd

Following is the data in the form of lists of team rankings ?

Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50]]

Creating a DataFrame with the above data and adding columns ?

import pandas as pd

Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50]]

dataFrame = pd.DataFrame(Team, columns=['Country', 'Rank', 'Points'])
print("Original DataFrame...")
print(dataFrame)

Original DataFrame...
       Country  Rank  Points
0        India     1     100
1    Australia     2      85
2      England     3      75
3  New Zealand     4      65
4 South Africa     5      50

Method 1: Using concat() (Recommended)

The modern approach is to use concat() instead of the deprecated append() method ?

import pandas as pd

# Original DataFrame
Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50]]
dataFrame = pd.DataFrame(Team, columns=['Country', 'Rank', 'Points'])

# Row to be appended as a list
myList = [["Sri Lanka", 6, 40]]

# Create new DataFrame from the list and concatenate
new_row = pd.DataFrame(myList, columns=['Country', 'Rank', 'Points'])
dataFrame = pd.concat([dataFrame, new_row], ignore_index=True)

print("Updated DataFrame after appending a row...")
print(dataFrame)

Updated DataFrame after appending a row...
       Country  Rank  Points
0        India     1     100
1    Australia     2      85
2      England     3      75
3  New Zealand     4      65
4 South Africa     5      50
5    Sri Lanka     6      40

Method 2: Using loc[] Indexer

You can also use the loc[] method to append a single row directly ?

import pandas as pd

# Original DataFrame
Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50],['Bangladesh', 6, 40]]
dataFrame = pd.DataFrame(Team, columns=['Country', 'Rank', 'Points'])

print("DataFrame...")
print(dataFrame)

# Row to be appended as a list (single row, not nested)
myList = ["Sri Lanka", 7, 30]

# Append using loc[] - assign to next available index
dataFrame.loc[len(dataFrame)] = myList

print("\nUpdated DataFrame after appending a row using loc...")
print(dataFrame)

DataFrame...
       Country  Rank  Points
0        India     1     100
1    Australia     2      85
2      England     3      75
3  New Zealand     4      65
4 South Africa     5      50
5   Bangladesh     6      40

Updated DataFrame after appending a row using loc...
       Country  Rank  Points
0        India     1     100
1    Australia     2      85
2      England     3      75
3  New Zealand     4      65
4 South Africa     5      50
5   Bangladesh     6      40
6    Sri Lanka     7      30

Comparison

Conclusion

Use pd.concat() for appending lists as rows to DataFrames, as it's the modern recommended approach. Use loc[] for simple single-row additions when performance matters.