How to format date string via multiple formats in python
I have three date formats: YYYY-MM-DD, DD.MM.YYYY, DD/MM/YYYY.
I have three date formats: YYYY-MM-DD, DD.MM.YYYY, DD/MM/YYYY.
I have an array of datetime objects, and I would like to find which element in the array is the closest to a given date (e.g datetime.datetime(2014,12,16))
I have a series within a DataFrame that I read in initially as an object, and then need to convert it to a date in the form of yyyy-mm-dd where dd is the end of the month.
I’m trying to plot a graph of dates on the x-axis and values on the y-axis. It works fine, except that I can’t get the range of the x-axis to be appropriate. The x-axis range is always Jan 2012 to Jan 2016, despite my dates being from today. I am even specifying that xlim should be the first and last date.
How do I check if a string can be parsed to a date?
I have two date ranges where each range is determined by a start and end date (obviously, datetime.date instances). The two ranges can overlap or not. I need the number of days of the overlap. Of course I can pre-fill two sets with all dates within both ranges and the perform a set intersection but this is possibly inefficient…is there a better way apart from another solution using a long if–elif section covering all cases?
I’m trying to figure out how to add 3 months to a date in a Pandas dataframe, while keeping it in the date format, so I can use it to lookup a range.
Given two datetimes (start_date and end_date), I’d like to generate a list of other datetimes between these two dates, the new datetimes being separated by a variable interval. e.g. every 4 days between 2011-10-10 and 2011-12-12 or every 8 hours between now and tomorrow 19p.m.
I have a Series object that has:
How can I change System Date, Time, Timezone in Python? Is there any module available for this?