Indexing and slicing

Accessing basic elements

Elements of a TimeSeries can be accessed just like their regular MaskedArray counterparts, using an integer, a sequence of integers, an array of integers or booleans, a slice, or a string corresponding to a field name (if the series has a structured dtype). In addition, a TimeSeries can be indexed by:

• a Date object;
• a sequence of Date objects;
• a DateArray object;
• a string representing a date;
• a sequence of strings representing dates.

In the last two cases, the strings are converted to a Date object with the same frequency as the TimeSeries instance.

If a single element is accessed on a TimeSeries with a standard dtype (without named fields), the result is either (i) a scalar if the element is not masked, or (ii) the constant masked if the corresponding mask element is True.

Accessing a single element of a TimeSeries with a structured data-type returns either (i) a numpy.void object if the element is not masked or (ii) a MaskedArray otherwise.

Accessing several elements at once always returns a TimeSeries object, with the same frequency as the input.

Examples

>>> monthly_start = ts.Date('M', '2005-01')
>>> series = ts.time_series(np.arange(12),
...                         start_date=monthly_start)

Accessing a single element with an integer:

>>> series[0]
0

Accessing a single element with a Date:

>>> series[monthly_start+6]
6

Accessing a single element with a string:

>>> series['2005-06-15']
5

Accessing several elements with a sequence of integers:

>>> series[[0, -1]]
timeseries([ 0 11],
   dates = [Jan-2005 Dec-2005],
   freq  = M)

Accessing several elements with a slice:

>>> series[-3:]
timeseries([ 9 10 11],
   dates = [Oct-2005 ... Dec-2005],
   freq  = M)

Accessing elements with an array of booleans:

>>> condition = (series < 7)
>>> series[condition]
timeseries([0 1 2 3 4 5 6],
   dates = [Jan-2005 ... Jul-2005],
   freq  = M)

Additional functions

Two functions provide a convenient way to access the first and last valid (not masked) elements of a TimeSeries:

first_unmasked_val
last_unmasked_val

Setting elements

Individual or multiple elements of a TimeSeries can be set the same way as for MaskedArray.

To mask one or several elements of a TimeSeries, they must be set to the masked constant.

Examples

>>> series
timeseries([ 0  1  2  3  4  5  6  7  8  9 10 11],
   dates = [Jan-2005 ... Dec-2007],
   freq  = M)

Masking the first and last elements of the series

>>> series[[0, -1]] = ma.masked
>>> series
timeseries([-- 1 2 3 4 5 6 7 8 9 10 --],
   dates = [Jan-2005 ... Dec-2005],
   freq  = M)

Setting the elements falling on the second quarter to 0

>>> series[series.quarter == 2] = 0
>>> series
timeseries([-- 1 2 0 0 0 6 7 8 9 10 --],
   dates = [Jan-2005 ... Dec-2005],
   freq  = M)