If then Else in numpy select-CodePudding

In my code with numpy.select below, I want to put the ELSE in condition section so that it will take care of all remaining scenario. How can I do it?

(The lambda is good to go)

df = pd.DataFrame({'id': [1,2,3,4,5,6,7,8,9],
                   'In': [111, 100, 31, 1100, 12, 33, 21, 32, 33],
                   'Out': [24, 52, 34, 95, 98, 54, 32, 20, 16]})

conditions = [
    df['In'] >100,
    df['Out'] > 50,
    (df['In']<df['Out']) & (df['Out']>20)
]

choices = [1, 2, 3]

df['check'] = np.select(conditions, choices, default=np.nan)
print(df)


# LAMBDA is good --------------------------------------------------------
df['lamda check'] = df[['In','Out']].apply(lambda x:
                       1 if x['In']>100 else
                       2 if x['Out']>50 else
                       3 if x['In']<x['Out'] and x['Out']>20 else
                       999, axis=1
                      )
print(df)

CodePudding user response：

If you want else 999, then set that as the default in np.select:

default : scalar
The element inserted in output when all conditions evaluate to False.

df['check'] = np.select(conditions, choices, default=999)