45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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from tools.statistics import extract, ressource
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def analyse(datas: list[dict]) -> plt.Figure:
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usage_completion: dict[str, int] = dict.fromkeys(ressource.usage.choices, 0)
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usage_count: dict[str, int] = dict.fromkeys(ressource.usage.choices, 0)
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for data in datas:
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usage = next(filter(
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lambda it: it[1]["checked"],
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data["surveys"]["question-usage-steam"]["choices"].items()
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))[0]
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usage_count[usage] += 1
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for survey in data["surveys"].keys():
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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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usage_completion[usage] += 1
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x = list(usage_completion.keys())
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y = (
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np.array(list(usage_completion.values()))
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/ np.array(list(usage_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 habitude d'utilisation")
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# bar chart
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axes.bar(x, y, color=ressource.usage.colors, edgecolor='black')
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axes.set_xticks(x)
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axes.set_xticklabels(ressource.usage.labels)
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axes.set_xlabel("Usage")
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axes.set_ylabel("Complétion")
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return figure
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