Dataframe when converted to numpy array gives float values with more decimal places

Question

I have a dataframe as so:

and the datatypes are as follows:

When I convert the dataframe to a numpy array, the result looks like this:

Why does this happen? if I convert the dtypes of all the columns to the same dtype by :

df = df.astype('float64')

then the result looks fine, but why does this happen?

Answer 1

Reason if float precision problem, possible solution should be Decimal if precision is important:

from decimal import Decimal

df = df.astype('float64').applymap(Decimal)