Birth Data¶

To obtain the population data for each year, we used two tables from StatCan:

1. 1999 - 2021:

   For past years, we used Table 17-10-00005-01 from StatCan.

   The *.csv file can be downloaded from here: 17100005-eng.zip

   and is saved as: LEAP/leap/original_data/17100005.csv

2. 2021 - 2065:

   For future years, we used Table 17-10-0057-01 from StatCan.

   The *.csv file can be downloaded from here: 17100057-eng.zip.

   and is saved as: LEAP/leap/original_data/17100057.csv

To run the data processing for the population data:

cd LEAP
python3 leap/data_generation/birth_data.py

This will update the following data files:

1. leap/processed_data/birth/birth_estimate.csv

2. leap/processed_data/birth/initial_pop_distribution_prop.csv

leap.data_generation.birth_data module¶

leap.data_generation.birth_data.get_projection_scenario_id(projection_scenario: str) → str[source]¶

Convert the long form of the projection scenario to the 2-letter ID.

Parameters:¶

projection_scenario: str¶

The long form of the projection scenario, e.g. Projection scenario M1.

Returns:¶

The 2-letter ID of the projection scenario, e.g. M1.

leap.data_generation.birth_data.filter_age_group(age_group: str) → bool[source]¶

Filter out grouped categories such as “Median”, “Average”, “All”, “to”, “over”.

Parameters:¶

age_group: str¶

The age group string.

Returns:¶

True if the age group is not a grouped category, False otherwise.

leap.data_generation.birth_data.load_past_births_population_data() → pandas.core.frame.DataFrame[source]¶

Load the past birth data from the CSV file.

Returns:¶

The past birth data. Columns:

• year: The year of the data.

• province: The 2-letter province ID.

• N: The total number of births in that year.

• prop_male: The proportion of births in that year that are male.

• projection_scenario: The projection scenario; all values are "past".

leap.data_generation.birth_data.load_projected_births_population_data(min_year: int) → pandas.core.frame.DataFrame[source]¶

Load the projected births data from the CSV file from StatCan.

Parameters:¶

min_year: int¶

The starting year for the projected data.

Returns:¶

The projected births data. Columns:

• year: The year of the data.

• province: The 2-letter province ID.

• N: The total number of births predicted for that year.

• prop_male: The proportion of predicted births in that year that are male.

• projection_scenario: The projection scenario, one of:

  • LG: low-growth projection

  • HG: high-growth projection

  • M1: medium-growth 1 projection

  • M2: medium-growth 2 projection

  • M3: medium-growth 3 projection

  • M4: medium-growth 4 projection

  • M5: medium-growth 5 projection

  • M6: medium-growth 6 projection

  • FA: fast-aging projection

  • SA: slow-aging projection

leap.data_generation.birth_data.load_past_initial_population_data() → pandas.core.frame.DataFrame[source]¶

Load the past initial population data from the CSV file.

Returns:¶

The past initial population data. Columns:

• year: The calendar year.

• province: The 2-letter province ID, e.g. BC.

• age: The age of the population.

• prop_male: The proportion of the population in that age group that are male.

• n_age: The total number of people in that age group for the given year, province, and projection scenario.

• n_birth: The total number of births in the given year, province, and projection scenario.

• prop: The proportion of the total number of people in that age group to the total number of births in that year.

• projection_scenario: The projection scenario; all values are “past”.

leap.data_generation.birth_data.load_projected_initial_population_data(min_year: int) → pandas.core.frame.DataFrame[source]¶

Load the projected initial population data from the CSV file.

Parameters:¶

min_year: int¶

The starting year for the projected data.

Returns:¶

The projected initial population data. Columns:

• year: The calendar year.

• province: The 2-letter province ID, e.g. BC.

• age: The age of the population.

• prop_male: The proportion of the population in that age group that are male.

• n_age: The total number of people in that age group for the given year, province, and projection scenario.

• n_birth: The total number of births in the given year, province, and projection scenario.

• prop: The proportion of the total number of people in that age group to the total number of births in that year.

• projection_scenario: The projection scenario, one of:

  • LG: low-growth projection

  • HG: high-growth projection

  • M1: medium-growth 1 projection

  • M2: medium-growth 2 projection

  • M3: medium-growth 3 projection

  • M4: medium-growth 4 projection

  • M5: medium-growth 5 projection

  • M6: medium-growth 6 projection

  • FA: fast-aging projection

  • SA: slow-aging projection

leap.data_generation.birth_data.generate_birth_estimate_data()[source]¶

Create/update the birth_estimate.csv file.

leap.data_generation.birth_data.generate_initial_population_data()[source]¶

Create/update the initial_pop_distribution_prop.csv file.