There is a Pandas dataframe: spi_rank country spi_score basic_human_needs foundations_of_wellbeing opportunity basic_nutri_med_care water_sanitation shelter personal_safety access_to_knowledge access_to_communications health_wellness environmental_quality personal_rights personal_freedom inclusiveness access_to_advanced_education 61 62.0 Russia 73.45 83.0 79.4 57.94 95.49 97.04 88.56 50.92 94.34 77.42 64.7 81.16 51.79 70.26 30.31 79.4 Write a function that finds the mean values of each column and transposes them to rows

import pandas as pd
df = pd.read_csv('SDG_data.csv')

def mean_row(data):
    
    df_2 = data[["basic_human_needs", "foundations_of_wellbeing", "opportunity", 
               "basic_nutri_med_care", "water_sanitation", "shelter", "personal_safety", 
               "access_to_knowledge", "access_to_communications", "health_wellness", 
               "environmental_quality", "personal_rights", "personal_freedom", 
               "inclusiveness", "access_to_advanced_education"]]
    mean_df = pd.DataFrame(df_2.mean(axis=0)).T
    return mean_df