In Pandas how do I convert a string of date strings to datetime objects and put them in a DataFrame?

Question

import pandas as pd
date_stngs = (\'2008-12-20\',\'2008-12-21\',\'2008-12-22\',\'2008-12-23\')

a = pd.Series(range(4),index = (range(4)))

for idx, date in enumerat         


        

Answer 1

A simple solution involves the Series constructor. You can simply pass the data type to the dtype parameter. Also, the to_datetime function can take a sequence of strings now.

Create Data

date_strings = ('2008-12-20','2008-12-21','2008-12-22','2008-12-23')

All three produce the same thing

pd.Series(date_strings, dtype='datetime64[ns]')
pd.Series(pd.to_datetime(date_strings))
pd.to_datetime(pd.Series(date_strings))

Benchmarks

The benchmarks provided by @waitingkuo are wrong. The first method is a bit slower than the other two, which have the same performance.

import datetime as dt
dates = [(dt.datetime(1960, 1, 1)+dt.timedelta(days=i)).date().isoformat() 
         for i in range(20000)] * 100

%timeit pd.Series(dates, dtype='datetime64[ns]')
730 ms ± 9.06 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)


%timeit pd.Series(pd.to_datetime(dates))
426 ms ± 3.45 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

%timeit pd.to_datetime(pd.Series(dates))
430 ms ± 5.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)