Python: Divide row in one DataFrame by all rows in another DataFrame

Question

I have two DataFrames as follows:

df1:
       A      B      C       D
index
    0  10000  20000  30000   40000

df2:
      time    type  A     B      C     D
index
    0 5/2020  unit  1000  4000   900   200
    1 6/2020  unit  7000  2000   600   4000

I want to divide df1.iloc[0] by all rows in df2 to get the following:

df:
      time    type  A     B    C       D
index
    0 5/2020  unit  10    5    33.33   200
    1 6/2020  unit  1.43  10   50      10

I tried to use df1.iloc[0].div(df2.iloc[:]) but that gave me NaNs for all rows other than the 0 index. Any suggestions would be greatly appreciated. Thank you.

BENY · Accepted Answer · 2022-06-22 00:51:21Z

1

Let us do

df2.update(df2.loc[:,df1.columns].rdiv(df1.iloc[0]))
df2
Out[861]: 
     time  type          A     B          C      D
0  5/2020  unit  10.000000   5.0  33.333333  200.0
1  6/2020  unit   1.428571  10.0  50.000000   10.0

answered Jun 22, 2022 at 0:51

BENY

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1 Comment

SomeDude Over a year ago

Actually both div or rdiv throws ZeroDivisionError if one of the divisor is 0, how to avoid it without complex logic of checking if zero is present in series or not. Is there any easy way?

Naveed · Accepted Answer · 2022-06-22 01:01:50Z

1

another way to do it, using numpy divide

df2.update(np.divide(df.to_numpy()[:,:], df2.loc[:,df.columns]))
df2

    time    type    A           B       C           D
0   5/2020  unit    10.000000   5.0     33.333333   200.0
1   6/2020  unit    1.428571    10.0    50.000000   10.0

answered Jun 22, 2022 at 1:01

Naveed

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Comments

SomeDude · Accepted Answer · 2022-06-22 01:04:01Z

1

You can use div.

df = df2.apply(lambda x:df1.iloc[0].div(x[df1.columns]), axis=1)

print(df):

               A     B          C      D
index                                   
0      10.000000   5.0  33.333333  200.0
1       1.428571  10.0  50.000000   10.0

edited Jun 22, 2022 at 1:04

answered Jun 22, 2022 at 0:55

SomeDude

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