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The next step is to create a list of indicators to generate. There are a
number of different visualization types available.
- table produce a table of indicator values
- chart produce a chart or graph using matplotlib
- map produce a choropleth map using matplotlib
- dataset_table produces a table for every specified year
with the values of each of the specified indicators.
First, the fields
that are common to each visualization type are described, and then examples and
specific fields are described for each visualization type. Every indicator
object takes the following parameters:
- source_data references the
SourceData object to be used for
this indicator (see Section 5.3.1).
- dataset_name is the name of the dataset that this indicator will be
computed for.
- years are the years that the indicator will be computed for.
This field is optional if the
SourceData object also
has a years field. The indicator years field overrides
the SourceData years field.
- name is the desired name of the indicator. This field is optional.
The default name is the indicator attribute, although
some indicators overload the default name. Name replaces
the old 'as' syntax.
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