New submission from seeking.that <[email protected]>:
Hi
python pandas bdate_range tz_convert() seems to have problems as it prints the
information incorrectly. Please clarity. The python script and the output is
shown below:
Two issues that can be highlighted here are:
1) Setting the timezone correctly to US/Pacific prints the dates correctly. But
the conversion causes the date calculations to be incorrect.
2. Minor issue just related to display. Though the API hasn't changed, the last
call has more information hh-mm-ss-xx-xx which is not there for the rest of the
calls with same format signature.
Thanks
SK
import pandas as pd
c5 = pd.bdate_range(start='1/1/2018', end = '1/31/2018')
print(c5)
c5 = c5.tz_localize('UTC')
print(c5)
c5 = c5.tz_convert('US/Pacific')
print(c5)
c6 = pd.bdate_range(start='1/1/2018', end = '1/31/2018')
print(c6)
c6 = c6.tz_localize('US/Pacific')
print(c6)
------
DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',
'2018-01-05', '2018-01-08', '2018-01-09', '2018-01-10',
'2018-01-11', '2018-01-12', '2018-01-15', '2018-01-16',
'2018-01-17', '2018-01-18', '2018-01-19', '2018-01-22',
'2018-01-23', '2018-01-24', '2018-01-25', '2018-01-26',
'2018-01-29', '2018-01-30', '2018-01-31'],
dtype='datetime64[ns]', freq='B')
DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',
'2018-01-05', '2018-01-08', '2018-01-09', '2018-01-10',
'2018-01-11', '2018-01-12', '2018-01-15', '2018-01-16',
'2018-01-17', '2018-01-18', '2018-01-19', '2018-01-22',
'2018-01-23', '2018-01-24', '2018-01-25', '2018-01-26',
'2018-01-29', '2018-01-30', '2018-01-31'],
dtype='datetime64[ns, UTC]', freq='B')
DatetimeIndex(['2017-12-31', '2018-01-01', '2018-01-02', '2018-01-03',
'2018-01-04', '2018-01-07', '2018-01-08', '2018-01-09',
'2018-01-10', '2018-01-11', '2018-01-14', '2018-01-15',
'2018-01-16', '2018-01-17', '2018-01-18', '2018-01-21',
'2018-01-22', '2018-01-23', '2018-01-24', '2018-01-25',
'2018-01-28', '2018-01-29', '2018-01-30'],
dtype='datetime64[ns, US/Pacific]', freq='B')
DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',
'2018-01-05', '2018-01-08', '2018-01-09', '2018-01-10',
'2018-01-11', '2018-01-12', '2018-01-15', '2018-01-16',
'2018-01-17', '2018-01-18', '2018-01-19', '2018-01-22',
'2018-01-23', '2018-01-24', '2018-01-25', '2018-01-26',
'2018-01-29', '2018-01-30', '2018-01-31'],
dtype='datetime64[ns]', freq='B')
DatetimeIndex(['2018-01-01 00:00:00-08:00', '2018-01-02 00:00:00-08:00',
'2018-01-03 00:00:00-08:00', '2018-01-04 00:00:00-08:00',
'2018-01-05 00:00:00-08:00', '2018-01-08 00:00:00-08:00',
'2018-01-09 00:00:00-08:00', '2018-01-10 00:00:00-08:00',
'2018-01-11 00:00:00-08:00', '2018-01-12 00:00:00-08:00',
'2018-01-15 00:00:00-08:00', '2018-01-16 00:00:00-08:00',
'2018-01-17 00:00:00-08:00', '2018-01-18 00:00:00-08:00',
'2018-01-19 00:00:00-08:00', '2018-01-22 00:00:00-08:00',
'2018-01-23 00:00:00-08:00', '2018-01-24 00:00:00-08:00',
'2018-01-25 00:00:00-08:00', '2018-01-26 00:00:00-08:00',
'2018-01-29 00:00:00-08:00', '2018-01-30 00:00:00-08:00',
'2018-01-31 00:00:00-08:00'],
dtype='datetime64[ns, US/Pacific]', freq='B')
----------
messages: 359156
nosy: Seeking.that
priority: normal
severity: normal
status: open
title: pandas tz_convert() seems to report incorrect date conversion
versions: Python 3.6
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Python tracker <[email protected]>
<https://bugs.python.org/issue39179>
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