CODEWITHSUNDEEP
pythonpandas
Jesper - jtk.eth
Jesper - jtk.eth

Reputation: 7446

Multiply rows in pandas dataframe

I have a dataframe with, say, 4 rows labeled r1 through r4 and 2 columns ("c1" and "c2"). The values in this dataframe/matrix are "aij" as in (pseudo-code):

dataframe =    c1  c2
            r1 a11 a12
            r2 a21 a22
            r3 a31 a32
            r4 a41 a42

I would now like to compute, in a very efficient way (think many many columns), the product of the rows.

More specifically, I would like to form a list with number of elements equal to number of columns which, as its ith element has the product of all rows:

list_ = [a11 * a21 * a31 * a41, a12 * a22 * a32 * a42]

In reality I have thousands of columns, but only around 4 rows.

I looked at dataframe's "sum(...)" function (with its "axis" argument) and it is something like that I need, but in a multiplication version. Not sure how to do this.

Upvotes: 2

Views: 4194

Answers (1)

EdChum
EdChum

Reputation: 393963

IIUC you can use prod which will calculate the product of all elements column-wise, you can then call tolist on the result as required:

In [23]:
df = pd.DataFrame(np.arange(12).reshape(4,3), columns=list('abc'))
df
​
Out[23]:
   a   b   c
0  0   1   2
1  3   4   5
2  6   7   8
3  9  10  11

In [26]:
df.prod()

Out[26]:
a      0
b    280
c    880
dtype: int64

In [25]:
df.prod().tolist()

Out[25]:
[0, 280, 880]

Upvotes: 2

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