I have a data frame that looks like this with timestamp in UTC seconds
open high low close volumeto
time
1530169200 6112.81 6120.62 6108.65 6111.63 2212255.01
1530170100 6111.63 6119.12 6106.45 6113.59 1572299.36
1530171000 6113.59 6116.44 6104.34 6110.23 2792660.45
1530171900 6110.23 6123.71 6106.49 6123.71 2314140.04
1530172800 6121.33 6133.24 6121.18 6129.52 2037071.96
When I try to write this to csv, this is what I get, I guess pandas is assuming that the supplied time is local time and offsetting it by 5 hours 30 mins but I have supplied UTC time
1530149400,6112.81,6120.62,6108.65,6111.63,2212255.01:
1530150300,6111.63,6119.12,6106.45,6113.59,1572299.36:
1530151200,6113.59,6116.44,6104.34,6110.23,2792660.45:
1530152100,6110.23,6123.71,6106.49,6123.71,2314140.04:
1530153000,6121.33,6133.24,6121.18,6129.52,2037071.96:
My code looks as shown below
csv_string = io.StringIO()
df.to_csv(csv_string, line_terminator=':', header=False, date_format='%s')
print(csv_string.getvalue())
How do I tell Pandas that I have supplied UTC time and do not wish to offset it while converting?