Changing concatenated date to datetime in Python

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I have an int value that I've parsed through a series of string dates in a dataframe that looks like this:

last_date_daily = int(old_df_daily.iloc[2,-1])
print(last_date_daily)

Which gives:

20190106

I simply want to convert this integer to a datetime format.

I've tried:

last_date_daily = pd.to_datetime(last_date_daily)

Which leaves me with a swap of time to date and an incorrect date:

1970-01-01 00:00:00.020190106

Is there an easy way to make this conversion without having to split the year, month, and day by a - or / string?

You might want to check out dateparser.

import dateparser
dateparser.parse('20190106', date_formats=['%Y%m%d'])
>>> datetime.datetime(2019, 1, 6, 0 0)

Python string to datetime - strptime(), Python string to datetime, Python strptime() function, Python convert string to date , python string to date, python time strptime(), parse string to date. Introduction One of the many common problems that we face in software development is handling dates and times. After getting a date-time string from an API, for example, we need to convert it to a human-readable format. Again, if the same API is used in different timezones, the conversion will be different. A good date-time library should convert the time as per the timezone. This is just one

to_datetime handles this case for strings:

In [11]: pd.to_datetime('20190106')
Out[11]: Timestamp('2019-01-06 00:00:00')

Python Concatenate String and int, Python Concatenate String and int, Python String concat with int, How to concatenate string and int in Python 3, Python string concat format(), %, f-strings. The easiest way is to convert int to a string using str() function. print(s + str(y)). First of all we have converted a date-time string into datetime object i.e., date_time_object. Then we converted datetime object into a timezone-enabled datetime object i.e., timezone_date_time_obj. Here we have defined the timezone as ‘Africa/Asmara’. So you can clearly see the time in output is 3 hours behind than UTC time.

It's really not hard to break an integer into different fields.

>>> datetime.datetime(last_date_daily//10000, (last_date_daily//100)%100, last_date_daily%100)
datetime.datetime(2019, 1, 6, 0, 0)

Date format is not working concatenate formula., I am having issues with concatenate formula. Its changing the date format to number automatically on B7. Cell format is already date. Any help will  This section is talking about how to keep date format in the CONCATENATE function in Excel. 1.Select a blank cell you will output the concatenation result, and enter the formula =CONCATENATE(TEXT(A2, "yyyy-mm-dd")," ", B2) ( A2 is the cell with date you will concatenate, and B2 is another cell you will concatenate) into it, and press the Enter key.

You should be casting your integer to a string before calling to_datetime() on it. It should be:

last_date_daily = pd.to_datetime(str(last_date_daily))

pandas.to_datetime, argint, float, str, datetime, list, tuple, 1-d array, Series DataFrame/dict-like If True , parses dates with the day first, eg 10/11/12 is parsed as 2012-11-10. Return UTC DatetimeIndex if True (converting any tz-aware datetime.datetime objects as https://docs.python.org/3/library/datetime.html#strftime-and-strptime-behavior. Return the local date corresponding to the POSIX timestamp, such as is returned by time.time (). This may raise OverflowError, if the timestamp is out of the range of values supported by the platform C localtime () function, and OSError on localtime () failure. It’s common for this to be restricted to years from 1970 through 2038.

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Work With Datetime Format in Python, Python provides a datetime object for storing and working with dates. convert columns in a pandas dataframe containing dates and times When plotting with ax.bar() and ax.scatter() , numpy is used to concatenate (a fancy  When a csv file is imported and a Data Frame is made, the Date time objects in the file are read as a string object rather a Date Time object and Hence it’s very tough to perform operations like Time difference on a string rather a Date Time object. Pandas to_datetime () method helps to convert string Date time into Python Date time object.

Comments
  • Try pd.to_datetime(last_date_daily.astype(str))
  • This works! But since it's an integer it has no attribute astype so I had to use last_date_daily = pd.to_datetime(str(last_date_daily)) instead. Thanks!