pandas replace

The `replace()` method in pandas is used to replace values in a DataFrame or Series object.

Syntax:

DataFrame.replace(to_replace=None, value=None, inplace=False, limit=None, regex=False, method='pad')

Parameters:

- `to_replace`: The value to be replaced.
- `value`: The value to replace `to_replace` with.
- `inplace`: If `True`, the original DataFrame or Series object will be modified. If `False`, a new object will be returned with the replacements made.
- `limit`: The maximum number of replacements to make. If `None`, all occurrences will be replaced.
- `regex`: If `True`, `to_replace` is treated as a regular expression.
- `method`: If `regex` is `True`, this parameter specifies the method to use to replace the values.

Example:

import pandas as pd

data = {'Name': ['John', 'Doe', 'Jane', 'Doe'],
        'Age': [25, 30, 35, 40],
        'Gender': ['M', 'M', 'F', 'F']}

df = pd.DataFrame(data)

# Replace 'Doe' with 'Smith'
df.replace(to_replace='Doe', value='Smith', inplace=True)

print(df)

Output:

   Name  Age Gender
0  John   25      M
1 Smith   30      M
2  Jane   35      F
3 Smith   40      F