CODEWITHSUNDEEP
pythonpython-3.xpandasdictionary
bernando_vialli
bernando_vialli

Reputation: 1019

.map removes values in my column that are not specified in the mapping

I have a variety of values in one of my columns in my pandas dataframe. Those include LIMITED LIABILITY CORP, CORPORATION, LIMITED LIABILITY PARTNER, Limited Liability Corporation

All I am trying to do is rename some of the values that are equivalent but are called differently. So here I want to rename Limited Liability Corporation as LIMITED LIABILITY CORP and same thing with the Partnership.

This is the code I have written using map:

Leads_updated['Business_Type'] = 
Leads_updated['Business_Type'].map({'Limited Liability Corporation': 
'LIMITED LIABILITY CORP', 'Limited Liability Partnership':'LIMITED LIABILITY 
 PARTNER'})

Now, it does properly change the values that I wanted to change, however, there are other values that I did not change in my code such as "Corporation" that are now gone from my pandas dataframe column.

Why is that and how can I fix it? Thank you!

Upvotes: 0

Views: 269

Answers (1)

sacuL
sacuL

Reputation: 51395

That is the expected behavior for map. It sounds like you're looking for replace instead, which will leave values unchanged if it is not in your dictionary keys:

Leads_updated['Business_Type'].replace({'Limited Liability Corporation': 'LIMITED LIABILITY CORP', 'Limited Liability Partnership':'LIMITED LIABILITY PARTNER'})

Upvotes: 1

Related Questions