import matplotlib.pyplot as plt import numpy as np from tools.statistics import extract, ressource def analyse(datas: list[dict]) -> plt.Figure: usage_completion: dict[str, int] = dict.fromkeys(ressource.usage.choices, 0) usage_count: dict[str, int] = dict.fromkeys(ressource.usage.choices, 0) for data in datas: usage = next(filter( lambda it: it[1]["checked"], data["surveys"]["question-usage-steam"]["choices"].items() ))[0] usage_count[usage] += 1 for survey in data["surveys"].keys(): # only scan survey mission if not survey.startswith("mission-"): continue if extract.mission_completed.extract(data, survey): usage_completion[usage] += 1 x = list(usage_completion.keys()) y = ( np.array(list(usage_completion.values())) / np.array(list(usage_count.values())) ) # prepare plotting figure: plt.Figure = plt.figure() axes = figure.add_subplot(1, 1, 1) axes.set_title("Nombre moyen de mission complété par habitude d'utilisation") # bar chart axes.bar(x, y, color=ressource.usage.colors, edgecolor='black') axes.set_xticks(x) axes.set_xticklabels(ressource.usage.labels) axes.set_xlabel("Usage") axes.set_ylabel("Complétion") return figure