Applying a function using 2 dataframe columns as arguments

Question

I want to apply a function that creates a column based on variables in 2 other columns.

One column 'SSPstaterank' returns the suburb ranking.
The second column 'SSPstaterank%' returns the suburb ranking percentile.

I thought this code would work, but it returns:

TypeError: ("'DataFrame' object is not callable", 'occurred at index 0')

def func1 (a,b):
    if a == 1:
        return 'the #1 suburb'
    elif b >= 0.95:
        return 'ranked top 5% of suburbs'
    elif b >= 0.9:
        return 'ranked top 10% of suburbs'
    else:
        return 'none'

df2['rankdescript'] = df2.apply(lambda x: df2(x['SSPstaterank'], x['SSPstaterank%']), axis=1)

jezrael · Accepted Answer · 2018-09-21 06:30:22Z

4

Use func1 instead df2:

df2['rankdescript'] = df2.apply(lambda x: func1(x['SSPstaterank'],x['SSPstaterank%']), axis=1)

Another solution with numpy.select should be faster:

df2 = pd.DataFrame({'SSPstaterank':[2,1,2,2,7],
                    'SSPstaterank%':[.99,.93,.93,.98,.23]})


m1 = df2['SSPstaterank'] == 1
m2 = df2['SSPstaterank%'] >= 0.95
m3 = df2['SSPstaterank%'] >= 0.9

masks = [m1, m2, m3]
vals = ['the #1 suburb','ranked top 5% of suburbs','ranked top 10% of suburbs']

df2['rankdescript'] = np.select(masks, vals, default='not matched')
print (df2)
   SSPstaterank  SSPstaterank%               rankdescript
0             2           0.99   ranked top 5% of suburbs
1             1           0.93              the #1 suburb
2             2           0.93  ranked top 10% of suburbs
3             2           0.98   ranked top 5% of suburbs
4             7           0.23                not matched

edited Sep 21, 2018 at 6:30

answered Sep 21, 2018 at 6:17

jezrael

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1 Comment

Ketil Tveiten Over a year ago

The second solution is probably faster; using df.apply(...,axis=1) is usually quite slow.

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