The correct answer is D. fillna().

The fillna() method is used to fill missing values in a DataFrame with specified values or a filling method. It takes two arguments: the value to fill in the missing values, and the method to use to fill in the missing values. The default value is NaN, and the default method is mean.

The melt() method is used to convert a DataFrame with columns of multiple values into a DataFrame with a single column of values and a column for each group.

The drop_duplicates() method is used to remove duplicate rows from a DataFrame.

Here is an example of how to use the fillna() method:

“`
import pandas as pd

df = pd.DataFrame({‘A’: [1, 2, 3, np.nan], ‘B’: [4, 5, 6, 7]})

df.fillna(0)

A B

0 1 4

1 2 5

2 3 6

“`

In this example, the fillna() method is used to fill in the missing values in the ‘A’ column with 0. The result is a DataFrame with no missing values.