Map a column from another data frame based on several conditions

Example data

Data

[Type]  [Cert Code]  [Cert Desc]  [Data Source]

HP      X1         Logic      Vendor

BA      X2         Disc       Employee

mappingID

[Cert Code]  [Cert Desc]

X3         Logic

X4         Disc

So X1 becomes X3 in data

I have this pandas code below which changes Certification Code to Old Certification Code based on description mappings in a second data frame.

The problem is I want to set two conditions whereby it does this only for rows with ‘vendor’ in ‘data source’ column and ‘hp’ in ‘type’ column. Can anyone help?

data['Certification Code'] = data['Certification Description'].map(mappingID.set_index('NEW Certification Description')['OLD Certification Code'])

I tried

filter = data[(data.Vendor == 'HP') & (data['Data Source'] == 'Vendor')]

I get

Data

[Type]  [Cert Code]  [Cert Desc]  [Data Source]

HP      X3           Logic      Vendor

BA                   Disc       Employee

data['Certification Code'] = filter['Certification Description'].map(mappingID.set_index('NEW Certification Description')['OLD Certification Code'])

The problem here it turns the Certification Code to blank for the other Vendors in the list.

Desired Outcome

Data

[Type]  [Cert Code]  [Cert Desc]  [Data Source]

HP      X3           Logic      Vendor

BA      X2           Disc       Employee