Python Pandas return DataFrame where value count is above a set number
pandas, python
Solution
So the issue here is indexing: value_counts() returns a Series indexed on 'Customers,' while zip_data_df seems to be indexed on something else. You can do something like:
cust_counts = zip_data_df['Customers'].value_counts().rename('cust_counts')
zip_data_df = zip_data_df.merge(cust_counts.to_frame(),
left_on='Customers',
right_index=True)
From there, you can select conditionally from zip_data_df like so:
zip_data_df[zip_data_df.cust_counts > 5]
Problem
I have a Pandas DataFrame, and I want to return the DataFrame only if that Customer Number occurs more than a set number of times. Here is a sample of the DataFrame: ``` 114 2017-04-26 1 7507 34 13 115 2017-04-26 3 77314 41 14 116 2017-04-27 7 4525 190 315 117 2017-04-27 7 5525 67 94 118 2017-04-27 1 6525 43 378 119 2017-04-27 3 7415 38 27 120 2017-04-27 2 7613 47 10 121 2017-04-27 2 77314 9 3 122 2017-04-28 1 227 17 4 123 2017-04-28 8 4525 205 341 124 2017-04-28 1 7415 31 20 125 2017-04-28 2 77314 8 2 ``` And here is if that customer occurs more than 5 times, using this code: ``` print(zip_data_df['Customers'].value_counts()>5) 7415 True 4525 True 5525 True 77314 True 6525 True 4111 True 227 True 206 False 7507 False 7613 False 4108 False 3046 False 2605 False 4139 False 4119 False ``` Now I expected if I did this: ``` print(zip_data_df[zip_data_df['Customers'].value_counts()>5]) ``` It would show me the whole DataFrame for customers that occur more than 5 times, but I got a Boolean error. I realize why it gives me an error now: one DataFrame is just telling me if that customer number occurs more than 5 times or not, and the other is showing me every time that customer number occurs. They don't match in length. But how do I get it so the dataframe will only return records where that customer occurs more than 5 times? I'm sure there is some simple answer I'm overlooking, but I appreciate any help you can get me.