30 lines
945 B
Python
Executable File
30 lines
945 B
Python
Executable File
import pandas as pd
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import seaborn as sns
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import matplotlib.pyplot as plt
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from scipy.stats import pearsonr
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if __name__ == '__main__':
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data = pd.read_csv('commit_analysis.csv')
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data['type'] = data['is_ml'].apply(lambda x: 'ML' if x else 'No ML')
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ylim = data['n_comments'].quantile(0.97)
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sns.catplot(x='type', y='n_comments', kind='box', data=data) \
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.set(title='Commenti in base al tipo di issue') \
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.set(xlabel='tipo') \
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.set(ylabel='numero di commenti') \
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.set(ylim=(0, ylim))
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plt.tight_layout()
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plt.savefig('../src/figures/comments.pdf')
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plt.close()
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ylim = data['words_mean'].quantile(0.97)
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sns.catplot(x='type', y='words_mean', kind='box', data=data) \
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.set(title='Parole medie in un commento') \
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.set(xlabel='tipo') \
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.set(ylabel='parole medie') \
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.set(ylim=(0, ylim))
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plt.tight_layout()
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plt.savefig('../src/figures/words.pdf')
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