Please provide python code to perform one hot encoding for below 6 categorical variables in dataset df

cat = ['Location_type', 'WH_capacity_size', 'zone', 'WH_regional_zone', 'wh_owner_type', 'approved_wh_govt_certificate']

#Replace Location_type Rural with 1 and Urban with 2
df['Location_type'] = df['Location_type'].replace({'Rural' : 1, 'Urban' :2})

#Replace WH_capacity_size Large with 2, Medium with 1 and Small with 0
df['WH_capacity_size'] = df['WH_capacity_size'].replace({'Large' :2, 'Mid' :1, 'Small' :0})

#Replace Zone East with 1, West with 2, North with 3 and South with 4
df['zone'] = df['zone'].replace({'East' : 1, 'West' :2, 'North' : 3, 'South' :4})

#Replace WH_regional_zone zone1 with 1, zone2 with 2,zone3 with 3,zone4 with 4 and zone5 with 5
df['WH_regional_zone'] = df['WH_regional_zone'].replace({'Zone 1' : 1, 'Zone 2' :2, 'Zone 3' :3, 'Zone 4' :4,'Zone 5' :5, 'Zone 6' :6})

#Replace wh_owner_type Company Owned with 1 and Rented with 2
df['wh_owner_type'] = df['wh_owner_type'].replace({'Company Owned' : 1, 'Rented' :2})

#Replace approved_wh_govt_certificate A+ with 5, A with 4, B+ with 3, B with 2, C with 1 and NA with 0
df['approved_wh_govt_certificate'] = df['approved_wh_govt_certificate'].replace({'A+' : 5, 'A' :4, 'B+' : 3, 'B' :2, 'C' : 1, 'NA' : 0})