Pandas Value Counts With Constraint For More Than One Occurance

Question

Working with the Wine Review Data from Kaggle here. I am able to return the number of occurrences by variety using value_counts()

However, I am trying to find a quick way to limit the results to varieties and their counts where there is more than one occurrence.

Trying df.loc[df['variety'].value_counts()>1].value_counts() and df['variety'].loc[df['variety'].value_counts()>1].value_counts() both return errors.

The results can be turned into a DataFrame and the constraint added there, but something tells me that there is a way more elegant way to achieve this.

Pilpul

try df['variety'].value_counts().loc[lambda x : x>1] – Weitzel

@WenThat did the trick. Do you have a link to the resource for using lambda in this way? Or I should ask. Can you use a lambda expression with loc as a constraint on the results anytime you are using an aggregate function? – Pilpul

Answer 1

@wen ansered this in the comments.

df['variety'].value_counts().loc[lambda x : x>1] 

Pilpul

This answer could benefit from a little bit of explenation. – Gravedigger

I think this provides answer to the question. Author was trying to find quick one-liner to filter out those unique data and see only data with more than 1 variety. This does the trick just nice! Thanks – Anemone

How do you group this set and create a value like "others"? – Lovellalovelock