pandas replace

In pandas, the `replace()` method is used to replace values in a DataFrame or Series.

Syntax:

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

Parameters:
- `to_replace`: Value to be replaced.
- `value`: Value to be replaced with.
- `inplace`: Whether to modify the DataFrame in place or return a new DataFrame.
- `limit`: Maximum number of replacements to make.
- `regex`: Whether to interpret `to_replace` as a regular expression.
- `method`: Method to use when replacing values. Default is 'pad', which replaces with the previous value.

Example:

import pandas as pd

# Create a sample DataFrame
data = {'Name': ['John', 'Sam', 'Emily', 'Jane', 'Tom'],
        'Age': [25, 30, 21, 28, 35],
        'Gender': ['M', 'M', 'F', 'F', 'M'],
        'Salary': [50000, 60000, 45000, 55000, 70000]}

df = pd.DataFrame(data)

# Replace all occurrences of 'M' with 'Male'
df.replace(to_replace='M', value='Male', inplace=True)

print(df)

Output:

    Name  Age Gender  Salary
0   John   25   Male   50000
1    Sam   30   Male   60000
2  Emily   21      F   45000
3   Jane   28      F   55000
4    Tom   35   Male   70000