# Write a Pandas program to split the following datasets into groups on customer id and calculate the number of customers starting with 'C', the list of all products and the difference of maximum purchase amount and minimum purchase amount.  import pandas as pd
pd.set_option('display.max_rows', None)
#pd.set_option('display.max_columns', None)
df = pd.DataFrame({
'ord_no':[70001,70009,70002,70004,70007,70005,70008,70010,70003,70012,70011,70013],
'purch_amt':[150.5, 270.65, 65.26, 110.5, 948.5, 2400.6, 5760, 1983.43, 2480.4, 250.45, 75.29, 3045.6],
'ord_date': ['05-10-2012','09-10-2012','05-10-2012','08-17-2012','10-09-2012','07-27-2012','10-09-2012','10-10-2012','10-10-2012','06-17-2012','07-08-2012','04-25-2012'],
'customer_id':['C3001','C3001','D3005','D3001','C3005','D3001','C3005','D3001','D3005','C3001','D3005','D3005'],
'salesman_id': [5002,5005,5001,5003,5002,5001,5001,5006,5003,5002,5007,5001]})
print("Original Orders DataFrame:")
print(df)
def customer_id_C(x):
    return (x.str[0] == 'C').sum()
result = df.groupby(['salesman_id'])\
  .agg(customer_id_start_C = ('customer_id', customer_id_C),
       customer_id_list = ('customer_id', lambda x: ', '.join(x)),
       purchase_amt_gap   = ('purch_amt', lambda x: x.max()-x.min())
      )
print("\nNumber of customers  starting with ‘C’, the list of all products and the difference of maximum purchase amount and minimum purchase amount:")
print(result)
