Lambda for multiple conditional functions in Dataframe

Question

Assuming I'm dealing with this dataframe:

Total	Retired	Cancelled	Remaining
100	10	20	70
150	160	30	-40
...	...	...	...

where

df['Remaining'] = df['Total'] - df['Retired'] - df['Cancelled']

My desired output should be like this from previous dataframe (to manually revise the negative ones in 'Remaining' to zeros):

Total	Retired	Cancelled	Remaining
100	10	20	70
190	160	30	0
...	...	...	...

I tried these lines, but it returns error. What did I do wrong?

df['Total'] = df.apply(lambda x: (x['Retired'] + x['Cancelled']) if x['Remaining'] < 0 else x['Total'])

(and do the previous calculation again for final output)

df['Remaining'] = df['Total'] - df['Retired'] - df['Cancelled']

please provide the full traceback when asking a question

Michael Delgado
– Michael Delgado

2022-06-09 16:50:50 +00:00
Commented Jun 9, 2022 at 16:50 — Michael Delgado
– Michael Delgado, Commented Jun 9, 2022 at 16:50

Beta · Accepted Answer · 2022-06-09 17:07:29Z

1

I tried to create your desired output example.

df = pd.DataFrame({'Total': [100, 120, 137, 210, 111],
                 'Retired': [20, 90, 60, 110,  170],
                 'Cancelled': [70, 10, 80, 50, 0]})

df = df.assign(Remaining = df['Total'] - df['Retired'] - df['Cancelled'])

df['Remaining'] = df['Remaining'].apply(lambda x: 0 if x < 0 else x)
df['Total'] = df.apply(lambda x: x['Total'] if x['Remaining'] > 0 else x['Retired'] + x['Cancelled'], axis = 1)
print(df)

edited Jun 9, 2022 at 17:07

answered Jun 9, 2022 at 16:49

Beta

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Comments

Quang Hoang · Accepted Answer · 2022-06-09 16:04:27Z

0

You need to pass axis=1 to apply so operation is row-wise. Otherwise, your x is a column of the dataframe.

But you can also do without apply:

df['Total'] = df['Total'].where(df['Remaining'] >= 0, df['Retired'] + df['Cancelled'])

answered Jun 9, 2022 at 16:04

Quang Hoang

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