Code Extender | Python

Python Code Enhancement for Filling Missing Values in Column B

Enhance existing Python code to fill missing values in column B with the mean of the column, ensuring data completeness and analysis accuracy.

Prompt

import pandas as pd
import numpy as np

data = {'A': [1, 2, np.nan], 'B': [3, np.nan, 5], 'C': ['a', 'b', 'c']}
df = pd.DataFrame(data)

# Fill missing values with mean of the column
df['A'].fillna(df['A'].mean(), inplace=True)

Answer

Extended Python Code Snippet

# Fill missing values with mean of the column for column B
df['B'].fillna(df['B'].mean(), inplace=True)

Instructions

To extend the existing code to fill missing values in column B with the mean of that column, you can simply add another line of code. This additional line accesses column B in the dataframe df and fills the missing values with the mean of column B. By incorporating this line, you are ensuring that all missing values in column B are replaced with the column's mean value, further enhancing data completeness and analysis accuracy.

Ensure to place this new line of code after the existing code snippet, keeping the flow intact. This extension follows the same structure and utilizes the pandas library functionality in Python for data manipulation.