CSV file handling with Pandas for text comparison

Question

I have this csv file called input.csv

KEY;Rate;BYld;DataAsOfDate
CH04;0.719;0.674;2020-01-29
CH03;1.5;0.148;2020-01-29

then I execute the following code:

import pandas as pd
input_df = pd.read_csv('input.csv', sep=";")
input_df.to_csv('output.csv', sep=";")

and get the following output.csv file

KEY;Rate;BYld;DataAsOfDate
CH04;0.7190000000000001;0.674;2020-01-29
CH03;1.5;0.14800000000000002;2020-01-29

I was hoping for and expecting an output like this: (to be able to use a tool like winmerge.org to detect real differences on each row) (my real code truly modifies the dataframe - this stack overflow example is for demonstration only)

KEY;Rate;BYld;DataAsOfDate
CH04;0.719;0.674;2020-01-29
CH03;1.5;0.148;2020-01-29

What is the idiomatic way with to achieve such an unmodified output with Pandas?

Answer 1

Python does not use traditional rounding to so as to prevent problems with bankers rounding. However, if being close is not a problem you could use the round function and replace the "2" with whichever number you would like to round to

d = [['CH04',0.719,0.674,'2020-01-29']]
df = pd.DataFrame(d, columns = (['KEY', 'Rate', 'BYld', 'DataAsOfDate']))
df['Rate'] = df['Rate'].apply(lambda x : round(x, 2))
df

Answer 2

Using @Prokos idea I changed the code like this:

import pandas as pd
input_df = pd.read_csv('input.csv', dtype='str',sep=";")
input_df.to_csv('str_output.csv', sep=";", index=False)

and that meets the requirement - all columns come out unchanged.