I have a timeserie containing dates in format dd/mm/yy and datetime in format dd/mm/yy hh:MM.
I am using pd.to_datetime to convert them to proper datetime format, which works fine. However, I would like to convert the datapoints in format dd/mm/yy to dd/mm/yy 00:00 or even better, dd/mm/yy 08:00.
How can I do that?
from datetime import date
from datetime import datetime
datetime.today().strftime('%Y-%m-%d') + " 8:00"
Output:
'2017-01-27 8:00'
Related
I have a date it look like this
2021-12-14T20:32:34Z
how can i convert it to someting like this
2021-12-14 20:32
If you want to do this using Pandas, you can use pandas to convert iso date to datetime object then strftime to convert timestamp into string format
import pandas as pd
import datetime
iso_date = '2021-12-14T20:32:34Z'
fmt = '%Y-%m-%d %H:%M'
pd.to_datetime(iso_date).strftime(fmt)
to apply it to a series of dates of DataFrame column you can replace iso_date with the series of dates and use this code
pd.to_datetime(iso_date).dt.strftime(fmt)
I have a string column in df which contains date in dd/MM/yyyy format and I want to convert that format to yyyy-MM-dd using with column
If you know you will have a consistent format in your column, you can pass this to 'to_datetime'.
You can try like below-
df['column_name'] = pd.to_datetime(df['column_name'], format='%d/%m/%y').dt.strftime('%Y-%m-%d')
Using python's datetime lib it can be done accordingly:
from datetime import datetime
date_string = '10/10/2000'
datetime_object = datetime.strptime(date_string, '%d/%m/%Y')
converted_date_string = datetime_object.strftime('%Y-%m-%d')
I have a list of date time strings like this.
16-Aug-2019
I want to convert the string to 2019-08-01 this date format, and I have tried on this code , but it's getting me an error.
formatd_date = datetime.strptime(formatd_date, '%y-%m-%d')
ValueError: time data 'As-of' does not match format '%y-%m-%d'
If any can help, it will be huge thank.
Convert to datetime format and then convert to string format you want to:
>>> from datetime import datetime
>>> a = "16-Aug-2019"
>>> datetime.strptime(a, "%d-%b-%Y").strftime("%Y-%m-%d")
'2019-08-16'
Documentation: https://docs.python.org/2/library/datetime.html#strftime-and-strptime-behavior
Just fails because %y is 2-digit year. Use %Y for 4-digit year.
I have an unusual datetime format in my dataset, which I need to convert to usable datetime object.
An example looks like: '1/3/2018 1:29:35 PM(UTC+0)'
I have tried to parse it with:
from dateutil.parser import parse
parse('1/3/2018 1:29:35 PM(UTC+0)')
but it doesn't recognize the format.
My current workaround is to parse the datetime column (the data is in pandas dataframe) using regex into two columns, like so:
and then depending on the value of the 'utc' column apply custom convert_to_eastern function.
I wonder if there is an easier way to accomplish it using datetime.datetime.strptime() ?
Following didn't work:
import datetime as dt
my_time='1/3/2018 1:29:35 PM(UTC+0)'
dt.datetime.strptime(my_time, '%m/%d/%Y %I:%M:%S %p(%z)')
Addition:
This is not a question: "How to convert UTC timezone into local timezone" My dataset has rows with UTC as well as Eastern time zone rows. The problem I have is that the format is not an ISO format, but some human-readable custom format.
Question: an easier way to accomplish it using datetime.datetime.strptime()
Split the datestring into parts: utc:[('1/3/2018 1:29:35 PM', '(UTC+0)', 'UTC', '+', '0')]
Rebuild the datestring, fixing the hour part padding with 0 to 2 digits.
I assume, there are no minutes in the UTC part, therefore defaults to 00.
If the datestring has more then 2 UTC digits, returns the unchanged datestring.
Note: The strptime format have to be %Z%z!
Documentation: strftime-and-strptime-behavior
from datetime import datetime
import re
def fix_UTC(s):
utc = re.findall(r'(.+?)(\((\w{3})(\+|\-)(\d{1,2})\))', s)
if utc:
utc = utc[0]
return '{}({}{}{})'.format(utc[0], utc[2], utc[3], '{:02}00'.format(int(utc[4])))
else:
return s
my_time = fix_UTC('1/3/2018 1:29:35 PM(UTC+0)')
date = datetime.strptime(my_time, '%m/%d/%Y %I:%M:%S %p(%Z%z)')
print("{} {}".format(date, date.tzinfo))
Output:
2018-01-03 13:29:35+01:00 UTC
Tested with Python: 3.4.2
The problem is with '+0' for your timezone 'UTC+0'. datetime only takes utc offset in the form of HHMM. Possible workaround:
import datetime as dt
my_time = '1/3/2018 1:29:35 PM(UTC+0)'
my_time=my_time.replace('+0','+0000')
dt.datetime.strptime(my_time, '%m/%d/%Y %I:%M:%S %p(%Z%z)')
It should be something like that:
import datetime as dt
my_time='1/3/2018 1:29:35 PM(UTC+0000)'
tmp = dt.datetime.strptime(my_time, '%m/%d/%Y %I:%M:%S %p(%Z%z)')
print(tmp)
Big "Z" for timezone (UTC, GMT etc), small "z" for delta. Also you should add more zeros to delta.
from datetime import datetime as dt
from datetime import date
clv['Date']=datetime.strptime(clv['Date'], "%m/%d/%Y").date()
You could use pd.to_datetime. After that you will convert your date string to Series of datetime64 dtype. Then you could access to date with dt.date:
clv['Date']=pd.to_datetime(clv['Date'], format="%m/%d/%Y").dt.date