# Write a Pandas program to drop those rows from a given DataFrame in which specific columns have missing values.  import pandas as pd
import numpy as np
pd.set_option('display.max_rows', None)
#pd.set_option('display.max_columns', None)
df = pd.DataFrame({
'ord_no':[np.nan,np.nan,70002,np.nan,np.nan,70005,np.nan,70010,70003,70012,np.nan,np.nan],
'purch_amt':[np.nan,270.65,65.26,np.nan,948.5,2400.6,5760,1983.43,2480.4,250.45, 75.29,np.nan],
'ord_date': [np.nan,'2012-09-10',np.nan,np.nan,'2012-09-10','2012-07-27','2012-09-10','2012-10-10','2012-10-10','2012-06-27','2012-08-17',np.nan],
'customer_id':[np.nan,3001,3001,np.nan,3002,3001,3001,3004,3003,3002,3001,np.nan]})
print("Original Orders DataFrame:")
print(df)
print("\nDrop those rows in which specific columns have missing values:")
result = df.dropna(subset=['ord_no', 'customer_id'])
print(result)
