sum of columns with condition in python

Question

I have a dataframe

id_command  command_status  stage   line_amount global_amount
61  ZeFMAA1 Pending     582.96  582.96
61  UbUjNAAV    Pending     70481.00    582.96
945 0bR8hEQAS   Pending     6400.00 12800.00

I would like to add a new column "decision" which is a boolean value (true or false) True if global_amount of a command is greater than 30% of the sum of line_amount of a command, and false if is not .

Can you help me to do this ?

Thanks

What is expected output from your sample data? Or which answer is correct? — jezrael
– jezrael, Commented May 28, 2019 at 9:11

anky · Accepted Answer · 2019-05-28 08:43:15Z

1

Based on :

sum of line_amount of a command

Use df.groupby() to group on the id_command and use transform to get sum distributed on each row. Then multiply by 0.3 and compare by series.gt():

df['decision']=df.global_amount.gt(df.groupby('id_command').line_amount.transform('sum')*0.3)
print(df)

   id_command command_status    stage  line_amount  global_amount  decision
0          61        ZeFMAA1  Pending       582.96         582.96     False
1          61       UbUjNAAV  Pending     70481.00         582.96     False
2         945      0bR8hEQAS  Pending      6400.00       12800.00      True

answered May 28, 2019 at 8:43

anky

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3 Comments

cyrinepersonne Over a year ago

thanks anky_91, but why you and @jezrael have different results? :o

anky Over a year ago

@cyrinepersonne the other result Jez calculates row by row, and this one calculates based on the sum of line amount taking id_command as a group.

jezrael Over a year ago

I believe your answer is correct, but rather wait for OP clarification.

jezrael · Accepted Answer · 2019-05-28 08:42:32Z

1

Use:

df['decision'] = df['global_amount'].gt(df['line_amount'].mul(.3))
print (df)
   id_command command_status    stage  line_amount  global_amount  decision
0          61        ZeFMAA1  Pending       582.96         582.96      True
1          61       UbUjNAAV  Pending     70481.00         582.96     False
2         945      0bR8hEQAS  Pending      6400.00       12800.00      True

answered May 28, 2019 at 8:42

jezrael

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