How to Use Drop Method in Pandas: Syntax and Examples

Use the drop method in pandas to remove rows or columns from a DataFrame by specifying labels. Set axis=0 to drop rows and axis=1 to drop columns. You can also use inplace=True to modify the DataFrame directly.

Syntax

The drop method syntax is:

• DataFrame.drop(labels, axis=0, inplace=False, errors='raise')

Explanation:

• labels: Single label or list of labels to drop.
• axis: 0 to drop rows, 1 to drop columns.
• inplace: If True, modifies the original DataFrame; otherwise returns a new one.
• errors: 'raise' to throw error if label not found, 'ignore' to skip.

python

DataFrame.drop(labels, axis=0, inplace=False, errors='raise')

Example

This example shows how to drop a row and a column from a DataFrame using drop.

python

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], 'City': ['NY', 'LA', 'Chicago']}
df = pd.DataFrame(data)

# Drop row with index 1 (Bob)
df_row_dropped = df.drop(1)

# Drop column 'City'
df_col_dropped = df.drop('City', axis=1)

print('Original DataFrame:')
print(df)
print('\nDataFrame after dropping row with index 1:')
print(df_row_dropped)
print('\nDataFrame after dropping column City:')
print(df_col_dropped)

Output

Original DataFrame:
      Name  Age     City
0    Alice   25       NY
1      Bob   30       LA
2  Charlie   35  Chicago

DataFrame after dropping row with index 1:
      Name  Age     City
0    Alice   25       NY
2  Charlie   35  Chicago

DataFrame after dropping column City:
      Name  Age
0    Alice   25
1      Bob   30
2  Charlie   35

Common Pitfalls

Common mistakes when using drop include:

• Forgetting to set axis=1 when dropping columns, which defaults to dropping rows.
• Not using inplace=True if you want to modify the original DataFrame.
• Trying to drop labels that do not exist without setting errors='ignore', which raises an error.

python

import pandas as pd

data = {'A': [1, 2], 'B': [3, 4]}
df = pd.DataFrame(data)

# Wrong: Trying to drop column 'C' without errors='ignore' (raises error)
try:
    df.drop('C', axis=1)
except KeyError as e:
    print(f'Error: {e}')

# Right: Use errors='ignore' to avoid error
new_df = df.drop('C', axis=1, errors='ignore')
print('\nDataFrame after trying to drop non-existent column C with errors=ignore:')
print(new_df)

Output

Error: "['C'] not found in axis"

DataFrame after trying to drop non-existent column C with errors=ignore:
   A  B
0  1  3
1  2  4

Quick Reference

Parameter	Description	Default
labels	Label or list of labels to drop	Required
axis	0 to drop rows, 1 to drop columns	0
inplace	Modify original DataFrame if True	False
errors	'raise' to throw error, 'ignore' to skip missing labels	'raise'

Key Takeaways

Use drop with axis=0 to remove rows and axis=1 to remove columns.

Set inplace=True to change the original DataFrame directly.

Use errors='ignore' to avoid errors when labels are missing.

Always specify labels correctly to avoid unexpected results.

Drop returns a new DataFrame by default unless inplace=True is set.