在熊猫队中用NBA统计数据创建一个三双栏目。

Question

I'm running into an issue with creating a very specific kind of boolean column in pandas. I'm working with NBA data and I want to create a column for when a player gets a triple double. This code works:

james_harden['trip_dub'] = (james_harden['points'] >= 10) & (james_harden['rebounds' >= 10) & (james_harden['assists'] >= 10)

james_harden['trip_dub'] = james_harden['trip_dub'].map(lambda x: 1 if x == True else 0)

However a triple double can be achieved with points, rebounds, and assists...points, rebounds, and blocks...rebounds, blocks, and assists...etc

I'm wondering if it's possible to write code to check if any combination of three columns out of a total of five are greater than or equal to 10...

So if i have columns a, b, c, d, e how do I check if (a >= 10 and b>= 10 and c>=10) OR (a >= 10 and d>=10 and e >= 10) ?

Answer 1

Assuming you have 5 statistics, and a triple-double is defined as at least 10 points in at least 3 statistics, you can use pd.DataFrame.sum along axis=1 :

stats = ['points', 'rebounds', 'assists', 'blocks', 'steals']
james_harden['trip_dub'] = (james_harden[stats] >= 10).sum(1) >= 3

The idea is james_harden[stats] >= 10 represents a Boolean dataframe and calling sum on it along columns sums the number of True values in each row . We then need only check the numbers in each row are greater than or equal to 3 .