How to reformat and rename values in a pandas dataframe

import pandas as pd

df = pd.DataFrame({'Discount':[10, 8, 20, 15, 10],
                   'Product':[' UMbreLla', '  maTress', 'BeDmintoN ', 'Shuttle', 'jaCket  '],
                   'Updated_Price':[880, 1250, 1450, 1550, 400],
                   'Date':['10/2/2011', '10/2/2011', '11/2/2011', '12/2/2011', '13/2/2011']})
df

	Discount	Product	Updated_Price	Date
0	10	UMbreLla	880	10/2/2011
1	8	maTress	1250	10/2/2011
2	20	BeDmintoN	1450	11/2/2011
3	15	Shuttle	1550	12/2/2011
4	10	jaCket	400	13/2/2011

here are some ways to (i) strip product names of whitespace and (ii) capitalize their first letter.

#Example 1
ls = df['Product'].tolist()
new_ls = [item.strip().capitalize() for item in ls]
df = df.drop(['Product'], axis=1)
df.insert(1,'Product_new', new_ls)
df

	Discount	Product_new	Updated_Price	Date
0	10	Umbrella	880	10/2/2011
1	8	Matress	1250	10/2/2011
2	20	Bedminton	1450	11/2/2011
3	15	Shuttle	1550	12/2/2011
4	10	Jacket	400	13/2/2011

#Example 2
df['Product'] = df['Product'].apply(lambda x: x.strip().capitalize())
df

	Discount	Product	Updated_Price	Date
0	10	Umbrella	880	10/2/2011
1	8	Matress	1250	10/2/2011
2	20	Bedminton	1450	11/2/2011
3	15	Shuttle	1550	12/2/2011
4	10	Jacket	400	13/2/2011

and the code below renames certain values using regex.

df.replace(to_replace=r'^Be', value='Ba', regex=True, inplace=True)
df

	Discount	Product_new	Updated_Price	Date
0	10	Umbrella	880	10/2/2011
1	8	Matress	1250	10/2/2011
2	20	Badminton	1450	11/2/2011
3	15	Shuttle	1550	12/2/2011
4	10	Jacket	400	13/2/2011