Count from a dataframe, then sort based on that count

Asked Jan 25 '19 at 16:12

Active Jan 25 '19 at 16:12

Viewed 29 times

I'm attempting to group a dataframe by products, get a count of each product, and then sort so the most frequent product is at the top of the resulting series.

Currently my code looks like:

    def return_most_products(self, df):
        most_products_series = df.groupby('Product')['Product'].count()
        most_products_series.sort_values()
        return most_products_list

Which works to sort the series by the 'Product' column alphabetically. As the count column doesn't have a header that I can see I'm stumped as how to indicate that I want to index, and sort, based on the count rather than the product.

asked Jan 25 '19 at 16:12

M. Goodman

3

df['Product].value_counts() will give you what you want. is the expected different to this output? – solver149 Jan 25 '19 at 16:18
That's exactly what I was looking for, thank you! – M. Goodman Jan 25 '19 at 16:20

Count from a dataframe, then sort based on that count

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