Question : string to date python
Answered by : muddy-magpie-hxql35972yuk
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)Source : https://stackabuse.com/converting-strings-to-datetime-in-python/ | Last Update : Mon, 08 Jun 20
Question : string to date python
Answered by : wild-worm-u5xi0jvyp5ou
# app.py
from datetime import datetime
date_str = '10-27-2020'
dto = datetime.strptime(date_str, '%m-%d-%Y').date()
print(type(dto))
print(dto)Source : https://appdividend.com/2022/01/29/how-to-convert-python-string-to-date/ | Last Update : Mon, 09 May 22
Question : python convert string to date
Answered by : luoskate
from datetime import datetime
datetime_object = datetime.strptime('Jun 1 2005 1:33PM', '%b %d %Y %I:%M%p')Source : https://stackoverflow.com/questions/466345/converting-string-into-datetime | Last Update : Sat, 06 Jun 20
Question : how to convert string to date object in python
Answered by : amit-kumar-0vytgw9s62vo
>>> import datetime
>>> datetime.datetime.strptime('24052010', "%d%m%Y").date()
datetime.date(2010, 5, 24)Source : https://stackoverflow.com/questions/2803852/python-date-string-to-date-object | Last Update : Tue, 01 Nov 22
Question : Convert string to datetime python
Answered by : lois-byrnes
Load libraries
import pandas as pd
from datetime import timedelta
# Loading dataset and creating duration column
url = 'https://drive.google.com/uc?id=1YV5bKobzYxVAWyB7VlxNH6dmfP4tHBui'
df = pd.read_csv(url, parse_dates = ['pickup_datetime', 'dropoff_datetime', 'dropoff_calculated'])
df["duration"] = pd.to_timedelta(df["duration"])
# Task 1 - filter to only rides with negative durations
df_neg = df[___["___"] < ___(___)]
# Task 2 - iterate over df_neg rows to find inconsistencies
count = 0
for i, row in df_neg.___(): # Compare minutes of dropoff_datetime and dropoff_calculated if row["___"].___ != row["___"].minute: # Print these two columns print(___[["dropoff_datetime", "dropoff_calculated"]]) # Task 3 - count number of rows having hour greater-equal than 12 if row["___"].___ >= ___: count ___
print(f"There are {count} rows in df_neg having hour greater-equal than 12.")Source : | Last Update : Tue, 20 Sep 22