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Convert pandas series to string and datetime object


On 9/21/17, Peter Otten <__peter__ at web.de> wrote:
> zljubisic at gmail.com wrote:
>
>> I have sliced the pandas dataframe
>>
>> end_date = df[-1:]['end']
>>
>> type(end_date)
>> Out[4]: pandas.core.series.Series
>>
>> end_date
>> Out[3]:
>> 48173   2017-09-20 04:47:59
>> Name: end, dtype: datetime64[ns]
>>
>> 1.	How to get rid of index value 48173 and get only "2017-09-20
> 04:47:59"
>> string? I have to call REST API with "2017-09-20 04:47:59" as a
>> parameter,
>> so I have to get string from pandas datetime64 series.
>> 2.	How to get rid of index value 48173 and get only datetime object
>> [something like datetime.datetime.strptime('2017-09-20 04:47:59',
>> '%Y-%m-%d %H:%M:%S')]. Later I will have to check if '2017-09-20
>> 04:47:59'
>> < datetime.datetime(2017,1,9)
>>
>> How to do these conversions?
>
> After a web search and some trial and error:
>
>>>> d = pd.DataFrame([[1, datetime.datetime.now()], [2,
> datetime.datetime.now()]], columns=["whatever", "end"])
>>>> d
>    whatever                        end
> 0         1 2017-09-21 22:36:52.342757
> 1         2 2017-09-21 22:36:52.349973
>
> [2 rows x 2 columns]
>>>> d["end"].astype(datetime.datetime).values[-1]
> datetime.datetime(2017, 9, 21, 22, 36, 52, 349973)

Or:

>>> d.iloc[-1]['end'].strftime('%Y-%m-%d %H:%M:%S')
'2017-09-22 09:03:40'

PS.
pandas is one of reasons why python is so popular these days. But
"there is only milion way how to do it" (and other unpythonic issues)
I see there every time I am looking at it. :)