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Lets say I have a dataframe like this

    A   B

0   a   b

1   c   d

2   e   f 

3   g   h

0,1,2,3 are times, a, c, e, g is one time series and b, d, f, h is another time series. I need to be able to add two columns to the orignal dataframe which is got by computing the differences of consecutive rows for certain columns.

So i need something like this

    A   B   dA

0   a   b  (a-c)

1   c   d  (c-e)

2   e   f  (e-g)

3   g   h   Nan

I saw something called diff on the dataframe/series but that does it slightly differently as in first element will become Nan.

1 Answer

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by (32.5k points)

Use diff and pass -1 as the periods argument:

>>> df = pd.DataFrame({"A": [9, 4, 2, 1], "B": [12, 7, 5, 4]})

>>> df["dA"] = df["A"].diff(-1)

>>> df

   A   B  dA

0  9  12   5

1  4   7   2

2  2   5   1

3  1   4 NaN

[4 rows x 3 columns]

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