# Write a Pandas program to find integer index of rows with missing data in a given dataframe.  
import pandas as pd
import numpy as np
df = pd.DataFrame({
    'school_code': ['s001','s002','s003','s001','s002','s004'],
    'class': ['V', 'V', 'VI', 'VI', 'V', 'VI'],
    'name': ['Alberto Franco','Gino Mcneill','Ryan Parkes', 'Eesha Hinton', 'Gino Mcneill', 'David Parkes'],
    'date_of_birth': ['15/05/2002','17/05/2002','16/02/1999','25/09/1998','11/05/2002','15/09/1997'],
    'weight': [35, None, 33, 30, 31, None]},
     index = ['t1', 't2', 't3', 't4', 't5', 't6'])
print("Original DataFrame:")
print(df)
index = df['weight'].index[df['weight'].apply(np.isnan)]
df_index = df.index.values.tolist()
print("\nInteger index of rows with missing data in 'weight' column of the said dataframe:")
print([df_index.index(i) for i in index])
