How to do exact decimal number calculation in pandas?

Question

My dataframe looks something like this:

import pandas as pd
df = pd.read_sql('select * from foo')

a  b  c
0.1 0.2 0.3
0.3 0.4 0.5

If I directly run df['a'] * df['b'] the result is not exact as I expected because of float number issues.

I tried

import Decimal

df['a'].apply(Decimal) * df['b'].apply(Decimal)

But when I inspect df['a'].apply(Decimal) with PyCharm, the column turns out to be something strange, here is just an example, not real numbers:

a
0.09999999999999999
0.30000000000001231

I wonder how to do exact multiplication in pandas.

whats the expected output because df['a'] * df['b'] works for me.. — iamklaus, Jun 17 '19 at 08:47
https://stackoverflow.com/questions/19473770/how-to-avoid-floating-point-errors — PV8, Jun 17 '19 at 08:52

score 0 · Accepted Answer · answered Jun 17 '19 at 09:09

The problem is not in pandas but in floating point inaccuracy: decimal.Decimal(0.1) is Decimal('0.1000000000000000055511151231257827021181583404541015625') on my 64 bits system.

A simple trick would be to first change the floats to strings, because pandas knows enough about string conversion to properly round the values:

x = df['a'].astype(str).apply(Decimal) * df['b'].astype(str).apply(Decimal)

You will get a nice Series of Decimal:

>>> print(x.values)
[Decimal('0.02') Decimal('0.12')]

So with exact decimal operations - which can matters if you process monetary values...

How to do exact decimal number calculation in pandas?

1 Answers1