Float64 and pandas: How to keep the number of significant digits in a file?

Question

I have a csv file like the following:

x y 
5.1 4.5
5.72 2.53
6.235 4.155

Please note the number of significant digits varies with the lines.

I would like to load it in python, make some calculations and save a new csv file with the number of digits by line respected. So, I want in output:

x y x+y x-y x*y
5.1 4.5 9.6 0.6 23.0 
5.72 2.53 8.25 3.19 14.47 
6.235 4.155 10.390 2.080 25.906

I did the following code:

import pandas as pd


# Import data from my file

#################################################################

# data_file = "Path.dat"

# data = open(data_file,"r")

# df = pd.read_csv(data,sep=' ')

##################################################################

# Creation of the dataframe without the file

df = pd.DataFrame({'x': {0: 5.1, 1: 5.72, 2: 6.235}, 'y': {0: 4.5, 1: 2.53, 2: 4.155}})

# Add new data

df.insert(2,'x+y',df['x'] + df['y'],True)

df.insert(3,'x-y',df['x'] - df['y'],True)

# Save the new file

# df.to_csv("Path.txt", index = False,sep=' ')

I have the following in output:

x y x+y x-y x*y
5.1 4.5 9.6 0.5999999999999996 22.95 
5.72 2.53 8.25 3.19 14.471599999999999 
6.235 4.155 10.39 2.08 25.906425000000002 

I read this question but it is answered to use the float_format argument which will "fix" a number of digits in all the file like that:

x y x+y x-y x*y
5.100 4.500 9.600 0.600 22.950 
5.720 2.530 8.250 3.190 14.472 
6.235 4.155 10.390 2.080 25.906