from collections import defaultdict import matplotlib.pyplot as plt import numpy as np from tools.statistics import extract def analyse(datas: list[dict]) -> plt.Figure: ages_duration: dict[int, int] = defaultdict(lambda: 0) ages_count: dict[int, int] = defaultdict(lambda: 0) # TODO: affichage en minutes ? for data in datas: age = extract.age.extract(data) ages_count[age] += 1 for survey in data["surveys"].keys(): # only scan survey mission if not survey.startswith("mission-"): continue ages_duration[age] += extract.mission_duration.extract(data, survey) x = list(ages_duration.keys()) y = ( np.array(list(ages_duration.values())) / np.array(list(ages_count.values())) ) # prepare plotting figure: plt.Figure = plt.figure() axes = figure.add_subplot(1, 1, 1) axes.set_title("Temps moyen passé par âge") # bar chart bins = np.arange(min(x), max(x), 1) axes.hist(x, bins, weights=y, edgecolor="black") axes.set_xlabel("Âge") axes.set_ylabel("Durée") return figure