100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
import argparse
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import numpy as np
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import scipy.stats as stats
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import matplotlib.pyplot as plt
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parser = argparse.ArgumentParser()
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parser.add_argument("-g", "--graph", action="store_true", default=False, help="Plot graph")
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parser.add_argument("-s", "--save", default="", help="Graph save location")
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args = parser.parse_args()
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graph = args.graph
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save = args.save
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colors = ["lightblue", "lightgreen", "lightcoral"]
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edge_colors = ["blue", "green", "red"]
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dataset = np.load("clean.npy")
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print(f"dataset shape: {dataset.shape}; analyzing column 11 (absence)")
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print("\tinteger value")
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print("")
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def analyze_absence(name: str, col: np.ndarray):
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absence_col = dataset[:, 11]
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tau, p = stats.kendalltau(absence_col, col)
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print(f"ken-tau for {name}: {tau}")
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print(f"p-value for {name}: {p}")
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if p > 0.05:
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print("statistically insignificant\n")
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else:
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print("statistically significant\n")
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return (absence_col, col), tau, p
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data_gpa, tau_gpa, p_gpa = analyze_absence("gpa", dataset[:, 2])
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data_math, tau_math, p_math = analyze_absence("math", dataset[:, 3])
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data_slovak, tau_slovak, p_slovak = analyze_absence("slovak", dataset[:, 4])
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data_english, tau_english, p_english = analyze_absence("english", dataset[:, 5])
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data = [data_gpa, data_math, data_slovak, data_english]
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taus = [tau_gpa, tau_math, tau_slovak, tau_english]
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ps = [p_gpa, p_math, p_slovak, p_english]
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if not graph:
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exit(0)
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grade_names = ["Priemer", "Matematika", "Slovenčina", "Angličtina"]
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grade_name_labels = ["Priemer známok", "Známka z matematiky", "Známka zo slovenčiny", "Známka z angličtiny"]
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fig, axs = plt.subplots(2, 2)
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fig.suptitle("Absencia", fontsize=18)
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fig.set_size_inches(12, 9)
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for j in range(2):
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for k in range(2):
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index = j * 2 + k
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step = 1 if index > 0 else 0.5
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if not index:
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x = data[index][0] # absence
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y = data[index][1] # grade
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axs[j, k].scatter(x, y)
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axs[j, k].set_xlabel("Počet vymeškaných hodín", fontweight="bold", fontsize=14)
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axs[j, k].set_ylabel(grade_name_labels[index], fontweight="bold", fontsize=14)
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axs[j, k].set_yticks(np.arange(1, 6))
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# trendline
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z = np.polyfit(x, y, 1)
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p = np.poly1d(z)
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axs[j, k].plot(x, p(x), color="gray")
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else:
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by_grade = list([data[index][0][data[index][1] == i + 1] for i in range(5)])
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# data[index][0] - absences
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# data[index][1] - grades
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# data[index][0][specific grade] - absences for that specific grande
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# loop 1 through 5 plug in ^^
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axs[j, k].set_xlabel(grade_name_labels[index], fontweight="bold", fontsize=14)
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axs[j, k].set_ylabel("Počet vymeškaných hodín", fontweight="bold", fontsize=14)
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axs[j, k].boxplot(by_grade, tick_labels=["1", "2", "3", "4", "5"])
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axs[j, k].set_title(grade_names[index], fontsize=16)
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tau = taus[index]
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p = ps[index]
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axs[j, k].text(0.01, 0.99, f"Tau τ: {tau:.4f}\np-val: {p:.4f}", ha="left", va="top",
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transform=axs[j, k].transAxes,
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fontweight="bold",
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fontsize=12)
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if p < 0.05:
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axs[j, k].set_facecolor("#ffff99")
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fig.tight_layout()
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if save != "":
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plt.savefig(save)
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else:
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plt.show()
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