How can I convert date from seconds to date format.
I have a table containing information about lat, long and time.
table
f_table['dt'] = pd.to_datetime(f_table['dt'])
f_table["dt"]
it results like this:
output
but the output is wrong actually the date is 20160628 but it converted to 1970.
My desired output:
24-April-2014
The unit needs to be nanoseconds, so you need to multiply with 1e9
f_table['dt'] = pd.to_datetime(f_table['dt'] * 1e9)
This should work.
#Split your string to extract timestamp, I am assuming a single space between each float
op = "28.359062 69.693673 5.204486e+08"
ts = float(op.split()[2])
from datetime import datetime
#Timestamp to datetime object
dt = datetime.fromtimestamp(ts)
#Datetime object to string
dt_str = dt.strftime('%m-%B-%Y')
print(dt_str)
#06-June-1986
Related
In my django project i have to convert a str variable passed as a date ("2021-11-10") to a datetime with timezone object for execute an ORM filter on a DateTime field.
In my db values are stored as for example:
2021-11-11 01:18:04.200149+00
i try:
# test date
df = "2021-11-11"
df = df + " 00:00:00+00"
start_d = datetime.strptime(df, '%Y-%m-%d %H:%M:%S%Z')
but i get an error due to an error about str format and datetime representation (are different)
How can i convert a single date string into a datetimeobject with timezone stated from midnight of the date value?
So many thanks in advance
It's not the way to datetime.strptime.
Read a little bit more here
I believe it will help you.
you should implement month as str and without "-".
good luck
Unable to convert DataFrame column to date time format.
from datetime import datetime
Holidays = pd.DataFrame({'Date':['2016-01-01','2016-01-06','2016-02-09','2016-02-10','2016-03-20'], 'Expenditure':[907.2,907.3,904.8,914.6,917.3]})
Holidays['Date'] = pd.to_datetime(Holidays['Date'])
type(Holidays['Date'])
Output: pandas.core.series.Series
Also tried
Holidays['Date'] = Holidays['Date'].astype('datetime64[ns]')
type(Holidays['Date'])
But same output
Output: pandas.core.series.Series
I think you are getting a bit mixed up. The dtypes of Holidays['Date'] is datetime64[ns]
Here's how I am checking.
from datetime import datetime
import pandas as pd
Holidays = pd.DataFrame({'Date':['2016-01-01','2016-01-06','2016-02-09','2016-02-10','2016-03-20'], 'Expenditure':[907.2,907.3,904.8,914.6,917.3]})
print ('Before converting : ' , Holidays['Date'].dtypes)
Holidays['Date'] = pd.to_datetime(Holidays['Date'])
print ('After converting : ' ,Holidays['Date'].dtypes)
The output is:
Before converting : object
After converting : datetime64[ns]
Thought I will also share some addition information for you around types and dtypes. See more info in this link for types-and-dtypes
I have this dataframe with start_date and end_date
and when i convert to json using to_json using this line
json_data = df.to_json(orient='records')
now if i print json_data the start_date is getting converted from yyyy-mm-dd to integer format
Please suggest a way so that the date format remains in yyyy-mm-dd format
Use DataFrame.select_dtypes for datetime columns, convert to format YYYy-MM-DD and last overwrite original data by DataFrame.update:
df.update(df.select_dtypes('datetime').apply(lambda x: x.dt.strftime('%Y-%m-%d')))
Then your solution working correct:
json_data = df.to_json(orient='records')
First set the format of your date, then set the date_format to 'iso':
df['start_date'] = pd.to_datetime(df['start_date']).dt.strftime('%Y-%m-%d')
df['end_date'] = pd.to_datetime(df['end_date']).dt.strftime('%Y-%m-%d')
data = df.to_json(orient='records', date_format='iso')
print(data)
[{"start_date":"2020-08-10","end_date":"2020-08-16"}]
Hi I have this DateTime format in our log "2019-09-19T15:12:59.943Z"
I want to convert this to custom DateTime format 2019-09-19 15:12:59
from datetime import datetime
timestamp = "2019-09-19T15:12:59.943Z"
dt_object = datetime.fromtimestamp(timestamp)
print("dt_object =", dt_object)
print("type(dt_object) =", type(dt_object))
which function shall I use for this
thanks
okay
This issue is related to custom DateTime formatting not related to timestamp.
because timestamp in python is an integer value, not a string value.
So you have a custom DateTime format which contains Zulu time format.
and you need to convert this Zulu DateTime format to custom DateTime format.
so, try this python script and its working fine on Python version 3.6
import datetime
d = datetime.datetime.strptime("2019-09-19T15:12:59.943Z","%Y-%m-%dT%H:%M:%S.%fZ")
new_format = "%Y-%m-%d"
d.strftime(new_format)
print(d)
or you can use this online fiddle to check the result
https://pyfiddle.io/fiddle/c7b8e849-c31a-41ba-8bc9-5436d6faa4e9/?i=true
I tried to convert a string into datetime object with yyyy/mm/dd format. using striptime() function it returns yyyy-mm-dd format with datetime.date type. I have used strftime() to convert into yyyy/mm/dd format but it returns a string type. How can we get a datetime type object with yyyy/mm/dd format?
datestr = '25/03/2019'
date_obj = datetime.strptime(datestr, '%d/%m/%Y').date()
print(date_obj)
date_formatted = date_obj.strftime('%Y/%m/%d')
print(type(datestr))
print(type(date_formatted))
I hope this help,
import datetime
date_time_str = '2018-06-29 08:15:27.243860'
date_time_obj = datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')
print('Date:', date_time_obj.date())
print('Time:', date_time_obj.time())
print('Date-time:', date_time_obj)
Also recommend you to read this article.