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This library provides a Python toolkit for analysing tariffs for electricity, gas and other utility services.
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Use cases include:
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- - assessing the bill savings associated with energy efficiency, solar or active load management
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+ - assessing the bill savings associated with energy efficiency, solar or load management
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- assessing the benefits of tariff switching
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Supported tariff components include:
@@ -47,7 +47,7 @@ Firstly define your tariff as a JSON data structure e.g. for a block tariff you
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}
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```
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- Next construct the Tariff, using a library called Odin
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+ Next construct the Tariff, using a library called [ Odin] ( https://www.github.com/python-odin/odin/ )
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``` python
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from odin.codecs import json_codec
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etc
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```
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- Next import the CSV using as a pandas DataFrame, making sure to include a parser to parse the datetimes appropriately:
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+ Next import the CSV using as a [ Pandas DataFrame] ( http://pandas.pydata.org/ ) , making sure to include a parser to parse the datetimes appropriately:
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``` python
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parser = lambda t : datetime.datetime.strptime(t, ' %d /%m/%Y %H:%M' )
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