query
a pythonic query language
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matplotlib powered data graphics.

Parameters:
AlcoholConsumptionLitersPerCapita, Country, ExpenditureOnHealthPerCapita, ExpenditureOnHealthPercentGDP, FemaleSalaryPercentLessThanMale, HospitalBedsPerThousand, InfantMortalityPerThousand, LifeExpectancyAtBirth, LifeExpectancyAtBirthFemale, LifeExpectancyAtBirthMale, ObesityPercent, ObesityPercentFemale, ObesityPercentMale, OutOfPocketExpenditureOnHealthPerCapita, OutOfPocketExpenditureOnHealthPercentTotal, PharmaceuticalExpenditurePerCapita, PhysiciansPerThousand, PsychiatricCareBedsPerThousand, PublicExpenditureOnHealthPerCapita, PublicExpenditureOnHealthPercentTotal, SuicidesPerMillion, TobaccoSmokersPercent, TobaccoSmokersPercentFemale, TobaccoSmokersPercentMale, Year, alcohol consumption liters per capita, country, expenditure on health per capita, expenditure on health percent GDP, hospital beds per 1000, infant mortality per 1000, life expectancy at birth, life expectancy at birth female, life expectancy at birth male, obesity percent, obesity percent female, obesity percent male, out of pocket expenditure on health per capita, out of pocket expenditure on health percent total, pharmaceutical expenditure per capita, physicians per 1000, psychiatric care beds per 1000, public expenditure on health per capita, public expenditure on health percent total, suicides per 100000, tobacco smokers percent, tobacco smokers percent female, tobacco smokers percent male, year

The PyQL query format is: fields @ conditions.
  fields is a field or a comma delimited list of fields.
 conditions is a condition or an and delimited list of conditions.

Both fields and conditions are made up of terms.
A term is a valid Python expression in a name space made up of: database parameters; any imported python modules; PyQL Aggregators such as Average (A), Sum (S), and Replace (R); and other domain specific terms.

About the OECD DatabaseSample Queries
This database was downloaded from the Organization for Economic Cooperation and Development.

In addition to the parameters listed above, this database is lightly customized by:

To see ExpenditureOnHealthPerCapita vs Year for the United States, use the PyQL:
Year,ExpenditureOnHealthPerCapita@Country='United States'

To see life expectancy as a function of per capita health care expenditure for Europe and the US, use the PyQL:
ExpenditureOnHealthPerCapita,LifeExpectancyAtBirth,Country@Country in Europe+['United States'] and Year=2013
Note how the country parameter in the third request field gives country flags for icons.

To see how health care costs as a percent of GDP have evolved for all countries in the OECD database, use the PyQL:
Year,ExpenditureOnHealthPercentGDP,Country@1