Tick to Ohlc 1hr data always start from 00:00:00 like 9:00:00 to 10:00:00. Even my data start from 9:15 it's not convert from 9:15 to 10:15....it just convert from 9:00:00 to 10:000
Solve this 1hr convert
Related
Could someone help me understand why these two queries are returning different results in bigquery?
select FORMAT_TIMESTAMP('%F %H:%M:%E*S', "2018-10-01 00:00:00" , 'Europe/London')
returns 2018-10-01 01:00:00
select PARSE_TIMESTAMP('%F %H:%M:%E*S', "2018-10-0100:00:00", "Europe/London")
returns 2018-09-30 23:00:00 UTC
As 2018-10-01 is during british summer time (UTC +1), I would've expected both queries to return 2018-09-30 23:00:00 UTC
The first is given a timestamp which is in UTC. It then converts it to the corresponding time in Europe/London. The return value is a string representing the time in the local timezone.
The second takes a string representation and returns a UTC timestamp. The representation is assumed to be in Europe/London.
So, the two functions are going in different directions, one from UTC to the local time and the other from the local time to UTC.
I need to convert the following varchar column to a 24 hr database time format in Teradata.
1:00 AM
6:45 PM
10:15 AM
9:30 PM
9:45 AM
8:30 PM
1:15 PM
Any pointers to existing solutions will be very helpful. I have not been able to find it.
Add the leading zero if missing and then cast using a format:
cast(lpad(col,8,'0') as time(0) format 'HH:MIBT')
The NYC bike and taxi datasets list the time when events happened in local time. Timestamps like 2018-01-07 10:30:00 means it was 10am in NY at the time.
When I ingest these timestamps into BigQuery, BigQuery assumes they are GMT - appending the incorrect timezone information.
How can I fix this?
2 choices:
Use DATETIME instead of TIMESTAMP - DATETIME has the same information than TIMESTAMP, except no timezone information is added.
Since this is NY, you can append the US/Eastern timezone when ingesting - it will correctly identify summer daylight saving changes and so on
For example:
SELECT TIMESTAMP('2018-3-10 10:00:00', 'US/Eastern')
, TIMESTAMP('2018-5-10 10:00:00', 'US/Eastern')
2018-03-10 15:00:00 UTC
2018-05-10 14:00:00 UTC
I have a file that contains forecasted events for the next two weeks. There is a datetime column which has the date and each 30 minute interval, and a time zone column.
I am using pytz to convert the different time zones (around 30+ unique ones) to UTC before loading them into a database. However, for the forecast file I am receiving an error:
NonExistentTimeError: 2016-10-16 00:00:00
Is there a way to go about this?
date interval time_zone
10/26/2016 22:30 US/Central
10/26/2016 22:30 US/Eastern
10/26/2016 23:00 America/Bogota
10/26/2016 23:00 Asia/Calcutta
Current code:
for tz in df['time_zone'].unique():
df.loc[df['time_zone'] == tz, 'datetime_utc'] = df.loc[df['time_zone'] == tz, 'datetime'].dt.tz_localize(tz).dt.tz_convert('UTC')
df['datetime_utc'] = df['datetime_utc'].dt.tz_localize(None)
Due to changes in daylight saving happening on the 16th October, 2016-10-16 00:00:00 really is a local time that does not exist for Brazil (It should instead read 2016-10-16 01:00:00)
I want historic date convert UTC 0 to UTC local in SQL. Like;
2012-11-23
2013-01-08
2014-02-23
But we have 2 different time zone. We use UTC +2 after last sunday in March and use UTC +3 after last sunday October. I need solution immediately guys. Please help me...
Try this:
SELECT CONVERT_TZ('your date ','+your time zone','+time zone you want');
SELECT CONVERT_TZ('2004-01-01 12:00:00','+02:00' ,'+03:00'); // in your case, from +2 to +3
See this link
If you need a dynamic thing, you'll need the timezone of each history (maybe you can store it in a separeted column), so I think you can do something like this:
SELECT CONVERT_TZ('your_date_column','local_timezone' ,'time_zone_column');