How do I filter a pandas DataFrame based on value counts?

Question

I'm working in Python with a pandas DataFrame of video games, each with a genre. I'm trying to remove any video game with a genre that appears less than some number of times in the DataFrame, but I have no clue how to go about this. I did find a StackOverflow question that seems to be related, but I can't decipher the solution at all (possibly because I've never heard of R and my memory of functional programming is rusty at best).

Help?

Answer 1

Use groupby filter:

In [11]: df = pd.DataFrame([[1, 2], [1, 4], [5, 6]], columns=['A', 'B'])  In [12]: df Out[12]:    A  B 0  1  2 1  1  4 2  5  6  In [13]: df.groupby("A").filter(lambda x: len(x) > 1) Out[13]:    A  B 0  1  2 1  1  4 

I recommend reading the split-combine-section of the docs.

Answer 2

Solutions with better performance should be GroupBy.transform with size for count per groups to Series with same size like original df, so possible filter by boolean indexing:

df1 = df[df.groupby("A")['A'].transform('size') > 1] 

Or use Series.map with Series.value_counts:

df1 = df[df['A'].map(df['A'].value_counts()) > 1]