为什么 date_range 给出的结果与 DataFrame Pandas 日期的索引 [] 不同？

Question

Here is a simple code with date_range and indexing [ ] I used with Pandas

period_start = '2013-01-01'
period_end = '2019-12-24'

print(pd.DataFrame ({'close':aapl_close,
        'returns':aapl_returns},index=pd.date_range(start=period_start,periods=6)))

print(pd.DataFrame ({'close':aapl_close,
            'returns':aapl_returns})[period_start:'20130110'])

date_range gives Nan results

            close  returns
2013-01-01    NaN      NaN
2013-01-02    NaN      NaN
2013-01-03    NaN      NaN
2013-01-04    NaN      NaN

Indexing gives correct results

                            close   returns
2013-01-02 00:00:00+00:00  68.732  0.028322
2013-01-03 00:00:00+00:00  68.032 -0.010184
2013-01-04 00:00:00+00:00  66.091 -0.028531

Based on how the dates are shown by date_range - I suppose the date format of date_range does not match the date format in the Pandas DataFrame.

1) Can you explaine please why it gives NaN?

2) What would you suggest to get a specific time range from the Panda DataFrame?

Answer 1

As I'm a beginner in Python and its libraries, I didn't understand that this question refers to the Quantopian library, not to Pandas.

I got a solution on their forum. All the times returned by methods on Quantopian are timezone aware with a timezone of 'UTC'. By default, the date_range method returns timezone naive dates. Simply supply the timezone information to date_range method. Like this

pd.DataFrame ({  
'close':aapl_close,  
'returns':aapl_returns,},  
index=pd.date_range(start=period_start, periods=6, tz='UTC'))

To get a specific date or time range in pandas perhaps the easiest is simple bracket notation. For example, to get dates between 2013-01-04 and 2013-01-08 (inclusive) simply enter this:

df = pd.DataFrame ({'close':aapl_close,  'returns':aapl_returns,})  
my_selected_dates = df['2013-01-04':'2013-01-08']

This bracket notation is really shorthand for using the loc method

my_selected_dates = df.loc['2013-01-04':'2013-01-08']

Both work the same but the loc method has a bit more flexibility. This notation also works with datetimes if desired.