how to fill missing values dataframe with mean

To fill missing values in a dataframe with the mean, you can use the fillna() method in Python. Here's an example of how to do it:

import pandas as pd

# Create a sample dataframe
data = {'A': [1, 2, None, 4, 5],
        'B': [None, 2, 3, None, 5],
        'C': [1, 2, 3, 4, None]}
df = pd.DataFrame(data)

# Fill missing values with the mean
df_filled = df.fillna(df.mean())

# Print the filled dataframe

This will replace all the missing values in the dataframe with the mean value of each column. The resulting dataframe, df_filled, will have the missing values filled with the mean.

Please note that this example assumes you have already imported the pandas library and created a dataframe named df with missing values. You can replace df with your actual dataframe name in the code.