CODEWITHSUNDEEP
pythonpandasdataframe
programmerInTraining04
programmerInTraining04

Reputation: 103

How can i add a column to a dataframe based on a conditional of another dataframe that has a different length, but shared column data

I have two dataframes of different lengths and different columns, but a shared column with the same identifying data. They look like this

observations DF:

index scientific_name park_name observations
0 name1 park1 10
1 name2 park2 12

species DF:

index scientific_name common_names category
0 name1 name1,name2 Mammal
1 name2 name1,name2 Vascular plant

I am trying to create a new column in the observatiosn DF called 'category' that is filled with data based on the shared scientific_names between both tables. I've tried using pd.merge but it doesn't fill the category column the way I want. Concat does not either. When i tried using a list comprehension it gave me a value error too. Any thoughts?

I tried using a list comprehension like so:

observations['category'] = [el for el in species['category'] if observations['scientific_name'] == species['scientific_name]]

This results in an error.

Upvotes: 1

Views: 47

Answers (1)

amance
amance

Reputation: 1770

If you only wanted to add the "category" column from species to observations based on the shared column "scientific_name", this should work.

observations = pd.merge(observations, species[['scientific_name', 'category']])

Upvotes: 1

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