I'm trying to generate a Pandas DataFrame where date_range is an index. Then save it to a CSV file so that the dates are written in ISO-8601 format.
import pandas as pd
import numpy as np
from pandas import DataFrame, Series
NumberOfSamples = 10
dates = pd.date_range('20130101',periods=NumberOfSamples,freq='90S')
df3 = DataFrame(index=dates)
df3.to_csv('dates.txt', header=False)
The current output to dates.txt is:
2013-01-01 00:00:00
2013-01-01 00:01:30
2013-01-01 00:03:00
2013-01-01 00:04:30
...................
I'm trying to get it to look like:
2013-01-01T00:00:00Z
2013-01-01T00:01:30Z
2013-01-01T00:03:00Z
2013-01-01T00:04:30Z
....................
Use datetime.strftime
and call map
on the index:
In [72]:
NumberOfSamples = 10
import datetime as dt
dates = pd.date_range('20130101',periods=NumberOfSamples,freq='90S')
df3 = pd.DataFrame(index=dates)
df3.index = df3.index.map(lambda x: dt.datetime.strftime(x, '%Y-%m-%dT%H:%M:%SZ'))
df3
Out[72]:
Empty DataFrame
Columns: []
Index: [2013-01-01T00:00:00Z, 2013-01-01T00:01:30Z, 2013-01-01T00:03:00Z, 2013-01-01T00:04:30Z, 2013-01-01T00:06:00Z, 2013-01-01T00:07:30Z, 2013-01-01T00:09:00Z, 2013-01-01T00:10:30Z, 2013-01-01T00:12:00Z, 2013-01-01T00:13:30Z]
Alternatively and better in my view (thanks to @unutbu) you can pass a format specifier to to_csv
:
df3.to_csv('dates.txt', header=False, date_format='%Y-%m-%dT%H:%M:%SZ')
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