Ayoub-Allali-HCP-Data 1.0.0

Easy access to Morocco's official demographic data (HCP – RGPH 2024) for data scientists and analysts.

Ayoub_Allali_HCP_Data

A Python library that gives data scientists and analysts instant access to Morocco's official demographic data published by the Haut-Commissariat au Plan (HCP) – General Population and Housing Census RGPH 2024.

Data source: hcp.ma – Recensement Général de la Population et de l'Habitat 2024.

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Installation

pip install Ayoub-Allali-HCP-Data

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Quick Start

import ayoub_allali_hcp_data as hcp

# Discover all datasets
hcp.info()

# --- Scalar values ---
print(hcp.get_population_legale())     # 36828330
print(hcp.get_nombre_menages())        # 9275038
print(hcp.get_taux_urbanisation())     # 0.628

# --- DataFrames ---
df = hcp.get_population_historique()
print(df)

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Available Datasets

Function	Description
get_population_legale()	Official legal population – 2024 (int)
get_nombre_menages()	Total number of households – 2024 (int)
get_taux_urbanisation()	Urbanisation rate – 2024 (float, e.g. 0.628)
get_population_historique()	Population & growth rate per census (1960–2024)
get_population_urbaine_rurale()	Urban / Rural counts & urbanisation rate (1960–2024)
get_structure_age()	Age-group distribution % – Ensemble / Urban / Rural (2024)
get_fecondite()	Total Fertility Rate by milieu (2024)
get_acces_reseaux_publics()	% HH with access to water, electricity, sanitation (2024)
get_taille_menage()	Average household size – Ensemble / Urban / Rural (2004–2024)

You can also use the generic load() function:

df = hcp.load("structure_age")

And list all dataset names:

hcp.list_datasets()
# ['acces_reseaux_publics', 'fecondite', 'nombre_menages', ...]

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Detailed Examples

Population history

import ayoub_allali_hcp_data as hcp
import matplotlib.pyplot as plt

df = hcp.get_population_historique()
print(df)
#    Année    Population  Taux d'accroissement
# 0   1960  1.162647e+07                   NaN
# 1   1971  1.537926e+07                  2.58
# 2   1982  2.041956e+07                  2.61
# 3   1994  2.607372e+07                  2.06
# 4   2004  2.989171e+07                  1.38
# 5   2014  3.384824e+07                  1.25
# 6   2024  3.682833e+07                  0.85

plt.plot(df["Année"], df["Population"] / 1e6, marker="o")
plt.title("Population du Maroc (millions)")
plt.xlabel("Année"); plt.ylabel("Population (M)")
plt.show()

Urban vs Rural breakdown

df = hcp.get_population_urbaine_rurale()
print(df)
#    Année    Urbain     Rural   Ensemble  Taux d'urbanisation (%)
# 0   1960   3389613   8236857  11626470                      29.2
# ...
# 6   2024  23110108  13718222  36828330                      62.8

Access to public utilities

df = hcp.get_acces_reseaux_publics()
print(df)
#        Réseaux publics  Urbain  Rural  Ensemble
# 0         Eau courante    97.1   54.6      82.9
# 1          Electricité    98.6   91.8      96.3
# 2       Assainissement    93.4    9.6      65.4

Fertility rate

df = hcp.get_fecondite()
print(df)
#       Milieu  Indice synthétique de fécondité
# 0   Ensemble                              2.0
# 1     Urbain                              1.8
# 2      Rural                              2.4

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License

MIT © Ayoub Allali

Data is published by HCP Morocco and is used here for educational and research purposes.