Pandas Dataframe to_csv format output

Question

I can't find a way to control the output of each column dataframe. From the following code:

df.to_csv('dfnc.txt', 
        sep=' ', 
        float_format='%.8f',
        cols=['cycle','passs','ip','lon','lat'],
        index=False)

I'm getting this:

1.00000000 1.00000000 543.00000000 23.15881870 -64.70485950
1.00000000 1.00000000 544.00000000 23.10356160 -64.64569150
1.00000000 1.00000000 545.00000000 23.04852510 -64.58650550
1.00000000 1.00000000 546.00000000 22.99370760 -64.52730150
1.00000000 1.00000000 547.00000000 22.93910770 -64.46807990

And I want this:

1 1 543 23.15881870 -64.70485950
1 1 544 23.10356160 -64.64569150
1 1 545 23.04852510 -64.58650550
1 1 546 22.99370760 -64.52730150
1 1 547 22.93910770 -64.46807990

Many thanks for the help.

CT Zhu · Accepted Answer · 2014-02-18 00:55:58Z

3

I think you can just convert the 1st to the 3rd columns to int64 before writing the CSV file (if you check the .types, I am sure they are all float64):

df[['cycle', 'passs', 'ip']]=df[['cycle', 'passs', 'ip']].astype(int64)

answered Feb 18, 2014 at 0:55

CT Zhu

54.6k18 gold badges125 silver badges136 bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

npires Over a year ago

You're right about .types, they were all float64. Your solution worked like a charm! Thanks a lot for the help!

Janine White Over a year ago

What if you want to control the decimal places in the float output?

Collectives™ on Stack Overflow

Pandas Dataframe to_csv format output

1 Answer 1

2 Comments

Collectives™ on Stack Overflow

Pandas Dataframe to_csv format output

1 Answer 1

2 Comments

Related