Transforming Datetime into Month, Day and Year

Convert Year/Month/Day to Day of Year in Python

Use datetime.timetuple() to convert your datetime object to a time.struct_time object then get its tm_yday property:

from datetime import datetime
day_of_year = datetime.now().timetuple().tm_yday  # returns 1 for January 1st

Convert datetime to MonthName DAY,YEAR

How about this:

select 
CONVERT(VARCHAR(12), dt, 107) AS [Mon DD, YYYY] 
from temp

Output:

Jan 16, 2013

Live Demo

Convert date format to 'Month-Day-Year'

You could use pandas.Series.dt.strftime (documentation) to change the format of your dates. In the code below I have a column with your old format dates, I create a new columns with this method:

import pandas as pd

df = pd.DataFrame({'old format': pd.date_range(start = '2020-01-01', end = '2020-06-30', freq = 'd')})
df['new format'] = df['old format'].dt.strftime('%m-%d-%Y')

Output:

  old format  new format
0 2020-01-01  01-01-2020
1 2020-01-02  01-02-2020
2 2020-01-03  01-03-2020
3 2020-01-04  01-04-2020
4 2020-01-05  01-05-2020
5 2020-01-06  01-06-2020
6 2020-01-07  01-07-2020
7 2020-01-08  01-08-2020
8 2020-01-09  01-09-2020
9 2020-01-10  01-10-2020

Transforming Datetime into month, day and year?

I don't know for

June 14th, 2010

But if you want

June 14, 2010

Ref how do i get name of the month in ruby on Rails? or this

Just do

@date = Time.now
@date.strftime("%B %d, %Y")

And for suffix use following

@date.strftime("%B #{@date.day.ordinalize}, %Y") # >>> Gives `June 18th, 2010`

How to convert year-month-day to just years in python?

Using just base Python (as you didn't specify that you have a pandas dataframe - pandas has specific functions to perform calculations with datetime objects):

from datetime import datetime
    
#takes as arguments the date as a string and an optional format string
def floatyear(str, fmtstr="%Y-%m-%d"):
    t = datetime.strptime(str, fmtstr)
    t_first = datetime(t.year, 1, 1, 0, 0, 0)
    t_last = datetime(t.year, 12, 31, 0, 0, 0)
    return t.year + ((t-t_first).days/(t_last-t_first).days)

print(floatyear("2018-10-24", "%Y-%m-%d"))

Sample output:

2018.8131868131868

Converting a date 'year - month - date' to only 'year and month' in r with SQL data

Up front, your attempt of as.Date(df$Posting_Date, format="%Y %m") seems backwards: the function as.Date is for converting from a string to a Date-class, and its format= argument is to identify how to find the year/month/day components of the string, not how you want to convert it later. (Note that in R, a Date is shown as YYYY-MM-DD. Always. Telling R you want a date to be just year/month is saying that you want to convert it to a string, no longer date-like or number-like. lubridate and perhaps other packages allow you to have similar-to-Date like objects.)

For df, one can just subset the strings without parsing to Date-class:

substring(df$Posting_Date, 1, 7)
# [1] "2020-05" "2020-10" "2021-10"

If you want to do anything number-like to them, you can convert to Date-class first, and then use format(.) to convert to a string with a specific format.

as.Date(df$Posting_Date)
# [1] "2020-05-28" "2020-10-09" "2021-10-19"
format(as.Date(df$Posting_Date), format = "%Y-%m")
# [1] "2020-05" "2020-10" "2021-10"

For df2, though, since it is numeric you need to specify an origin= instead of a format=. I'm inferring that these are based off of epoch, so

as.Date(df2$Posting_Date, origin = "1970-01-01")
# [1] "2020-05-28" "2020-10-09" "2021-10-19"
format(as.Date(df2$Posting_Date, origin = "1970-01-01"), format = "%Y-%m")
# [1] "2020-05" "2020-10" "2021-10"

Note that R stores Date (and POSIXct, incidentally) as numbers internally:

dput(as.Date(df2$Posting_Date, origin = "1970-01-01"))
# structure(c(18410, 18544, 18919), class = "Date")

Convert date (month, day, year, time) to Datetime format in python

If you insist on comparing as strings...

from datetime import datetime

a = "2016-04-15T04:08:03.000+0000"
b = "Apr 15, 2016, 4:08:03 AM"

a = datetime.strptime(a, '%Y-%m-%dT%H:%M:%S.%f%z')
b = datetime.strptime(b, '%b %d, %Y, %I:%M:%S %p')
b = b.replace(tzinfo=a.tzinfo)

print(a.isoformat())
print(b.isoformat())

Extracting just Month and Year separately from Pandas Datetime column

If you want new columns showing year and month separately you can do this:

df['year'] = pd.DatetimeIndex(df['ArrivalDate']).year
df['month'] = pd.DatetimeIndex(df['ArrivalDate']).month

or...

df['year'] = df['ArrivalDate'].dt.year
df['month'] = df['ArrivalDate'].dt.month

Then you can combine them or work with them just as they are.

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