Population
Population is defined as all nationals present in, or temporarily absent from a country, and aliens permanently settled in a country. This indicator shows the number of people that usually live in an area. Growth rates are the annual changes in population resulting from births, deaths and net migration during the year.
Total population includes the following:
- national armed forces stationed abroad; merchant seamen at sea;
- diplomatic personnel located abroad;
- civilian aliens resident in the country;
- displaced persons resident in the country.
However, it excludes the following:
- foreign armed forces stationed in the country;
- foreign diplomatic personnel located in the country;
- civilian aliens temporarily in the country.
Population projections are a common demographic tool. They provide a basis for other statistical projections, helping governments in their decision making.
By default the data comes from the Global Macro Database (GMDB), which returns a single total population series per country, in millions of people. Set gmdb_source=False for the OECD series, which breaks the total down by gender, giving a Population, Men and Women series for each country, and reports a plain count of persons rather than millions. Both are annual, and the OECD source uses the historical (observed) series rather than its projections.
See definition: https://data.oecd.org/pop/population.htm
Also known as: demographic data, census data.
Population in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_population_statistics as shown below.
from financetoolkit import Economics
economics = Economics(start_date='2010-01-01', end_date='2019-01-01')
economics.get_population_statistics(countries='Japan')
Or, after setting up the Finance Toolkit MCP, ask:
How did the population of Japan develop from 2010 to 2019?
Which returns:
| Japan | |
|---|---|
| 2010 | 128.043 |
| 2011 | 127.831 |
| 2012 | 127.552 |
| 2013 | 127.333 |
| 2014 | 127.262 |
| 2015 | 127.11 |
| 2016 | 126.933 |
| 2017 | 126.706 |
| 2018 | 126.443 |
| 2019 | 126.167 |
Parameters
get_population_statistics accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
countries | list[str] | str | None | The countries to include in the data. Defaults to None. | ["United States", "Germany"] |
gmdb_source | bool | None | Whether to get the data from the Global Macro Database (GMDB). Defaults to None, which falls back to the gmdb_source set on the Economics class (True by default). | False |
rolling | int | The rolling window size to use for smoothing the data (simple moving average). Defaults to None. | 4 |
trailing | int | The trailing window size to use for summing the data over trailing periods (e.g. a trailing-4-quarter sum). Defaults to None. | 4 |
growth | bool | Whether to return the growth data or the actual data. Defaults to False. | True |
lag | int | The number of periods to lag the data by. Defaults to 1. | 4 |
standardize | bool | Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False. | True |
rounding | int | None | The number of decimals to round the results to. Defaults to None. | 2 |
gmdb_forecasts | bool | Whether to include the years the Global Macro Database projects, from the IMF’s World Economic Outlook, up to five years ahead. Only applies to data from the Global Macro Database. Defaults to False, which ends a series with its last observation. | True |