Visualizing age pyramid

The age pyramid is helpful to quickly visualize the age and gender distributions in a cohort.

Load a synthetic dataset

plot_age_pyramid uses the "person" table:

from eds_scikit.datasets.synthetic.person import load_person

df_person = load_person()
df_person.head()

| | person_id | gender_source_value | birth_datetime | |---|-----------|---------------------|----------------| | 0 | 0 | m | 2010-01-01 | | 1 | 1 | m | 1938-01-01 | | 2 | 2 | f | 1994-01-01 | | 3 | 3 | m | 1994-01-01 | | 4 | 4 | m | 2004-01-01 |

Visualize age pyramid

Basic usage

By default, plot_age_pyramid will compute age as the difference between today and the date of birth:

from eds_scikit.plot.age_pyramid import plot_age_pyramid

plot_age_pyramid(df_person)

Advanced parameters

Further configuration can be provided, including :

datetime_ref : Choose the reference to compute the age from. It can be either a single datetime (string or datetime type), an array of datetime (one reference for each patient) or a string representing a column of the input dataframe
return_array: If set to True, return a dataframe instead of a chart.

import pandas as pd
from datetime import datetime
from eds_scikit.plot.age_pyramid import plot_age_pyramid

dates_of_first_visit = pd.Series([datetime(2020, 1, 1)] * df_person.shape[0])
plot_age_pyramid(df_person, datetime_ref=dates_of_first_visit)

Please check the documentation for further details on the function's parameters.