Convert number to date python

Python and Matlab quite often have integer date representations as follows:

733828.0 733829.0 733832.0 733833.0 733834.0 733835.0 733836.0 733839.0 733840.0 733841.0

these numbers correspond to some dates this year. Do you guys know which function can convert them back to YYYYMMDD format?

thanks a million!

John Topley

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asked Apr 12, 2010 at 15:21

0

The datetime.datetime class can help you here. The following works, if those values are treated as integer days (you don't specify what they are).

>>> from datetime import datetime
>>> dt = datetime.fromordinal(733828)
>>> dt
datetime.datetime(2010, 2, 25, 0, 0)
>>> dt.strftime('%Y%m%d')
'20100225'

You show the values as floats, and the above doesn't take floats. If you can give more detail about what the data is (and where it comes from) it will be possible to give a more complete answer.

answered Apr 12, 2010 at 15:26

Peter HansenPeter Hansen

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Since Python example was already demonstrated, here is the matlab one:

>> datestr(733828, 'yyyymmdd')

ans =

20090224

Also, note that while looking similar these are actually different things in Matlab and Python:

Matlab
A serial date number represents the whole and fractional number of days from a specific date and time, where datenum('Jan-1-0000 00:00:00') returns the number 1. (The year 0000 is merely a reference point and is not intended to be interpreted as a real year in time.)

Python, datetime.date.fromordinal
Return the date corresponding to the proleptic Gregorian ordinal, where January 1 of year 1 has ordinal 1.

So they would differ by 366 days, which is apparently the length of the year 0.

answered Apr 12, 2010 at 15:27

SilentGhostSilentGhost

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Dates like 733828.0 are Rata Die dates, counted from January 1, 1 A.D. (and decimal fraction of days). They may be UTC or by your timezone.

Julian Dates, used mostly by astronomers, count the days (and decimal fraction of days) since January 1, 4713 BC Greenwich noon. Julian date is frequently confused with Ordinal date, which is the date count from January 1 of the current year (Feb 2 = ordinal day 33).

So datetime is calling these things ordinal dates, but I think this only makes sense locally, in the world of python.

answered Jun 21, 2012 at 17:46

1

Is 733828.0 a timestamp? If so, you can do the following:

import datetime as dt
dt.date.fromtimestamp(733828.0).strftime('%Y%m%d')

PS

I think Peter Hansen is right :)

I am not a native English speaker. Just trying to help. I don't quite know the difference between a timestamp and an ordinal :(

answered Apr 12, 2010 at 15:25

satorusatoru

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Here is the syntax that you may use to convert integers to datetime in Pandas DataFrame:

df['DataFrame Column'] = pd.to_datetime(df['DataFrame Column'], format=specify your format)

Note that the integers must match the format specified. Later, you’ll see several scenarios for different formats.

Step 1: Gather the data to be converted to datetime

To start, gather the data that you’d like to convert to datetime.

For example, the following dataset contains 3 different dates (with a format of yyyymmdd), when a store might be opened or closed:

Step 2: Create the DataFrame

Next, create the DataFrame to capture the above dataset in Python:

import pandas as pd

values = {'dates':  [20210305,20210316,20210328],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

print (df)
print (df.dtypes)

As you may see, the data type is integer for the values under the ‘dates’ column:

      dates  status
0  20210305  Opened
1  20210316  Opened
2  20210328  Closed
dates      int64
status    object
dtype: object

Step 3: Convert the integers to datetime in Pandas DataFrame

Now you may use the template below in order to convert the integers to datetime in Pandas DataFrame:

df['DataFrame Column'] = pd.to_datetime(df['DataFrame Column'], format=specify your format)

Recall that for our example, the date format is yyyymmdd.

In that case, the date format can be represented as follows:

format='%Y%m%d'

As indicated previously, the integer data (yyyymmdd) must match the format specified (%Y%m%d). You may refer to the following source for the different formats that you may apply.

For our example, the complete code to convert the integers to datetime would be:

import pandas as pd

values = {'dates':  [20210305,20210316,20210328],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

df['dates'] = pd.to_datetime(df['dates'], format='%Y%m%d')

print (df)
print (df.dtypes)

Run the code in Python, and you’ll see that the data type for the ‘dates’ is now datetime:

       dates  status
0 2021-03-05  Opened
1 2021-03-16  Opened
2 2021-03-28  Closed
dates     datetime64[ns]
status            object
dtype: object

Converting Additional Formats

Let’s suppose that the dates are now formatted as yymmdd:

In that case, the date format would now contain ‘y‘ in lower case:

format='%y%m%d'

So the complete Python code would look as follows:

import pandas as pd

values = {'dates':  [210305,210316,210328],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

df['dates'] = pd.to_datetime(df['dates'], format='%y%m%d')

print (df)
print (df.dtypes)

As before, the integers would get converted to datetime:

       dates  status
0 2021-03-05  Opened
1 2021-03-16  Opened
2 2021-03-28  Closed
dates     datetime64[ns]
status            object
dtype: object

Now let’s suppose that your integers contain both the dates and times:

In that case, the format that you should specify is:

format='%Y%m%d%H%M%S'

So the full Python code would be:

import pandas as pd

values = {'dates':  [20210305093000,20210316093000,20210328200000],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

df['dates'] = pd.to_datetime(df['dates'], format='%Y%m%d%H%M%S')

print (df)
print (df.dtypes)

You’ll now get the datetime format:

                dates  status
0 2021-03-05 09:30:00  Opened
1 2021-03-16 09:30:00  Opened
2 2021-03-28 20:00:00  Closed
dates     datetime64[ns]
status            object
dtype: object

You may also want to check the following guide for the steps to convert strings to datetime in Pandas DataFrame.

How do you convert a number to a date in Python?

How do I convert a number to a date in a DataFrame in Python?

How do you convert a 5 digit number to a date in Python?

How do you convert input to date in Python?