def query_stat_all(): return sqlite.query("url_stat.db", "select * from single")
draw_line(xy_s[1], xy_s[0], 'Frequency', 'Response Time', 'Response Time Distribution', 'r') def distribute_seaborn(data_s, y_label, x_label, title): sns.set(color_codes=True) sns.set(font_scale=1.5) sns.distplot(np.array(data_s)) sns.plt.xlabel(x_label) sns.plt.ylabel(y_label) sns.plt.title(title) sns.plt.show() if __name__ == '__main__': login_s = sqlite.query('../web/url_stat.db', "select * from single where url like '%Login'") touch_s = sqlite.query('../web/url_stat.db', "select * from single where url like '%Touch%'") clean_s = sqlite.query( '../web/url_stat.db', "select * from single where url like '%SessionClean%'") play_back_s = sqlite.query( '../web/url_stat.db', "select * from single where url like '%Playback%'") real_play_s = sqlite.query( '../web/url_stat.db', "select * from single where url like '%RealPlay%'") long_time_s = sqlite.query( '../web/url_stat.db', "select * from single where url like '%LongTime%'")
print(xy_s[1]) draw_line(xy_s[1], xy_s[0], 'Frequency', 'Response Time', 'Response Time Distribution', 'r') def distribute_seaborn(data_s, y_label, x_label, title): sns.set(color_codes=True) sns.set(font_scale=1.5) sns.distplot(np.array(data_s)) sns.plt.xlabel(x_label) sns.plt.ylabel(y_label) sns.plt.title(title) sns.plt.show() if __name__ == '__main__': login_s = sqlite.query('../web/url_stat.db', "select * from single where url like '%Login'") touch_s = sqlite.query('../web/url_stat.db', "select * from single where url like '%Touch%'") clean_s = sqlite.query('../web/url_stat.db', "select * from single where url like '%SessionClean%'") play_back_s = sqlite.query('../web/url_stat.db', "select * from single where url like '%Playback%'") real_play_s = sqlite.query('../web/url_stat.db', "select * from single where url like '%RealPlay%'") long_time_s = sqlite.query('../web/url_stat.db', "select * from single where url like '%LongTime%'") result_s = [login_s, touch_s, clean_s, play_back_s, real_play_s, long_time_s] login_avg_s = [0.0, 0.0, 0.0] touch_avg_s = [0.0, 0.0, 0.0] clean_avg_s = [0.0, 0.0, 0.0] play_back_avg_s = [0.0, 0.0, 0.0] real_play_avg_s = [0.0, 0.0, 0.0] long_time_avg_s = [0.0, 0.0, 0.0]