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+# Loading a TCPD time series in Python
+
+The ``load_dataset.py`` file contains example code to load a time series as a 
+``TimeSeries`` object.
+
+```python
+>>> from load_dataset import TimeSeries
+>>> ts = TimeSeries.from_json('../../datasets/ozone/ozone.json')
+```
+
+To export the time series as a [pandas 
+DataFrame](https://pandas.pydata.org/pandas-docs/stable/getting_started/dsintro.html#dataframe), 
+simply use:
+
+```python
+>>> ts.df
+     t  Total Emissions
+0    0         380000.0
+1    1         400000.0
+2    2         440000.0
+3    3         480000.0
+4    4         510000.0
+5    5         540000.0
+...
+```
+
+The ``TimeSeries`` instance ``ts`` has an integer time axis at ``ts.t`` and 
+the observations at ``ts.y``. The time axis is zero-based by default. If you 
+prefer to use a one-based indexing, simply run:
+
+```python
+>>> ts.make_one_based()
+>>> ts.df
+     t  Total Emissions
+0    1         380000.0
+1    2         400000.0
+2    3         440000.0
+3    4         480000.0
+4    5         510000.0
+5    6         540000.0
+...
+```
+
+Many of the time series in TCPD have date or datetime labels for the time 
+axis. This axis can be retrieved using:
+
+```python
+>>> ts.datestr
+array(['1961', '1962', '1963', '1964', '1965', '1966', '1967', '1968',
+        ...
+       '2009', '2010', '2011', '2012', '2013', '2014'], dtype='<U4')
+```
+
+which uses the date format stored in ``ts.datefmt``.
+
+```python
+>>> ts.datefmt
+'%Y'
+```