How to use mutiple arithmetic functions in multiple columns in pandas dataframe

Question

I have a pandas dataframe and three lists as follows.

list1 = ['n3', 'n5', 'n7']
list2 = ['n1', 'n2', 'n4', 'n11', 'n12']
list3 = ['n6', 'n8', 'n9', 'n10']

item  n1  n2  n3  n4  n5  n6  n7  n8  n9  n10  n11  n12
item1  1   6   7  8   9   1    6   8   8    9   9    5
item2  1   6   7  6   9   1    8   8   8    9   9    5

I want to select the column names in the three lists and perform the following arithmetic functions.

list1: addition
list2: take absolute of the number (i.e. abs(n)) and addition
list3: take inverse of the number (i.e. 1/n) and addition

For example, if we take item1:

list1:add columns n3, n5, n7 i.e. 7+9+6 = 22
list2: take abosulte and add columns n1, n2, n4, n11, n12 i.e. abs(1)+abs(6)+abs(8)+abs(9)+abs(5) = 29
list3: take inverse and add columns n6, n8, n9, n10 i.e. 1/1 + 1/8 + 1/8 + 1/9 = 1.3611

Now, I want to add the sums separately and total to the dataframe.

item  n1  n2  n3  n4  n5  n6  n7  n8  n9  n10  n11  n12   list1_sum  list2_sum  list3_sum total_sum
item1  1   6   7  8   9   1    6   8   8    9   9    5      xxx  xxx  xxx  xxx
item2  1   6   7  6   9   1    8   8   8    9   9    5      xxx  xxx  xxx  xxx

I was able to do list1 as follows.

df['list1_sum'] = df[list1].sum(axis=1)

However, I could not find how to do the remaining operations.

I am happy to provide more details if needed.

Pandas is very handy with arithmetic operations, you are close to the solution. Use df[list2].abs().sum(1) and (1/df[list3]).sum(1) — Bharath M Shetty
– Bharath M Shetty, Commented Apr 17, 2019 at 5:26

jezrael · Accepted Answer · 2019-04-17 05:38:18Z

3

Use DataFrame.abs and DataFrame.rdiv for divide from right side:

df['list1_sum'] = df[list1].sum(axis=1)
df['list2_sum'] = df[list2].abs().sum(axis=1)
df['list3_sum'] = df[list3].rdiv(1).sum(axis=1)
#same like 
#df['list3_sum'] = (1 / df[list3]).sum(axis=1)

df['total_sum'] = df[['list1_sum','list2_sum','list3_sum']].sum(axis=1)
print (df)
    item  n1  n2  n3  n4  n5  n6  n7  n8  n9  n10  n11  n12  list1_sum  \
0  item1   1   6   7   8   9   1   6   8   8    9    9    5         22   
1  item2   1   6   7   6   9   1   8   8   8    9    9    5         24   

   list2_sum  list3_sum  total_sum  
0         29   1.361111  52.361111  
1         27   1.361111  52.361111

edited Apr 17, 2019 at 5:38

answered Apr 17, 2019 at 5:32

jezrael

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Comments

Rajat Jain · Accepted Answer · 2019-04-17 06:03:10Z

1

You can also try this:

df[list2].apply(lambda x: 1/x.sum(), axis=1)

df[list2].apply(lambda x: 1.0/x.sum(), axis=1)

However, jezrael's answer is faster

answered Apr 17, 2019 at 6:03

Rajat Jain

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