How to Use append in pandas: Syntax, Example, and Tips

In pandas, use the append() method to add rows from one DataFrame or Series to another. It returns a new DataFrame with the combined data without changing the original. Note that append() is deprecated since pandas 1.4.0; use pd.concat() instead for newer code.

Syntax

The append() method is called on a DataFrame to add rows from another DataFrame or Series. It returns a new DataFrame with the rows added.

• other: The DataFrame or Series to append.
• ignore_index: If True, the new DataFrame will reset the index to default integers.
• verify_integrity: If True, checks for duplicate indexes and raises an error if found.
• sort: If True, sorts columns if columns differ.

python

DataFrame.append(other, ignore_index=False, verify_integrity=False, sort=False)

Example

This example shows how to append one DataFrame to another and reset the index to get a clean combined DataFrame.

python

import pandas as pd

# Create first DataFrame
df1 = pd.DataFrame({
    'Name': ['Alice', 'Bob'],
    'Age': [25, 30]
})

# Create second DataFrame
df2 = pd.DataFrame({
    'Name': ['Charlie', 'Diana'],
    'Age': [35, 40]
})

# Append df2 to df1 and reset index
combined = df1.append(df2, ignore_index=True)
print(combined)

Output

      Name  Age
0    Alice   25
1      Bob   30
2  Charlie   35
3    Diana   40

Common Pitfalls

One common mistake is expecting append() to modify the original DataFrame. It does not; it returns a new DataFrame. Another issue is using append() repeatedly in a loop, which is inefficient. Instead, collect DataFrames in a list and use pd.concat() once.

Also, since pandas 1.4.0, append() is deprecated and will be removed in future versions. Use pd.concat() for better performance and future compatibility.

python

import pandas as pd

# Inefficient way (legacy)
df = pd.DataFrame({'A': [1, 2]})
for i in range(3, 6):
    df = df.append({'A': i}, ignore_index=True)
print(df)

# Efficient way using concat
frames = [pd.DataFrame({'A': [1, 2]})]
for i in range(3, 6):
    frames.append(pd.DataFrame({'A': [i]}))
df_concat = pd.concat(frames, ignore_index=True)
print(df_concat)

Output

   A
0  1
1  2
2  3
3  4
4  5
   A
0  1
1  2
2  3
3  4
4  5

Quick Reference

Summary tips for using append() in pandas:

• Use append() to add rows from another DataFrame or Series.
• It returns a new DataFrame; original is unchanged.
• Set ignore_index=True to reset the index after appending.
• For multiple appends, use pd.concat() for better speed.
• Note: append() is deprecated; prefer pd.concat().

Key Takeaways

The append() method adds rows from one DataFrame to another and returns a new DataFrame.

append() does not change the original DataFrame; assign the result to a new variable.

Use ignore_index=True to reset the index after appending for a clean DataFrame.

Avoid using append() repeatedly in loops; use pd.concat() for better performance.

append() is deprecated since pandas 1.4.0; use pd.concat() for future-proof code.