42 lines
1.1 KiB
Python
42 lines
1.1 KiB
Python
from collections import defaultdict
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import matplotlib.pyplot as plt
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import numpy as np
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from tools.statistics import extract
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def analyse(datas: list[dict]) -> plt.Figure:
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ages_completion: dict[int, int] = defaultdict(lambda: 0)
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ages_count: dict[int, int] = defaultdict(lambda: 0)
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for data in datas:
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age = extract.age.extract(data)
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ages_count[age] += 1
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for survey, survey_data in data["surveys"].items():
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# only scan survey mission
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if not survey.startswith("mission-"):
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continue
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if extract.mission_completed.extract(data, survey):
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ages_completion[age] += 1
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x = list(ages_completion.keys())
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y = (
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np.array(list(ages_completion.values()))
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/ np.array(list(ages_count.values()))
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)
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# prepare plotting
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figure: plt.Figure = plt.figure()
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axes = figure.add_subplot(1, 1, 1)
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axes.set_title("Nombre moyen de mission complété par âge")
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# bar chart
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bins = np.arange(min(x), max(x), 1)
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axes.hist(x, bins, weights=y, edgecolor="black")
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axes.set_xlabel("Âge")
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axes.set_ylabel("Complétion")
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return figure
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