Difference between rows in pandas

Difference between rows in pandas

I have data in csv which i am reading with pandas. The data is of this format-

name company income saving A AA 100 10 B AA 200 20

I wish to create a new row with name A, company AA and income and saving being difference of A and B.

Expected output-

name company income saving A AA -100 -10

There are only 2 rows of data? Please check how to provide a great pandas example as well as how to provide a minimal, complete, and verifiable example
– jezrael
Jul 2 at 6:56

I have updated by question. There are lots of rows. I shall be able to do that if i can figure out this minimal example
– throwaway073
Jul 2 at 7:05

So what should contain the result from the third row? What should happen if company differs? What was your approach and why did it fail?
– Mr. T
Jul 2 at 7:08

The companies won't differ. I shall take care by filtering. Basically i can't figure out when i take difference, I don't want the first 2 columns to subtract as they are string. I only want the columns having numerical value to subtract. (all columns after 2nd column are numerals)
– throwaway073
Jul 2 at 7:14

Can you add 2, 3 new rows to sample data with expected output?
– jezrael
Jul 2 at 7:26

1 Answer
1

I believe need:

print (df) name company income saving 0 A AA 100 10 1 B AA 200 20 2 C AA 300 40 #for select columns by names df1 = df[['name','company']].join(df[['income','saving']].diff(-1)) #for select columns by positions #df1 = df.iloc[:, :2].join(df.iloc[:, 2:].diff(-1)) print (df1) name company income saving 0 A AA -100.0 -10.0 1 B AA -100.0 -20.0 2 C AA NaN NaN

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