diff --git a/data1_analysis.py b/data1_analysis.py new file mode 100644 index 0000000..6eb2d03 --- /dev/null +++ b/data1_analysis.py @@ -0,0 +1,188 @@ +# data1_analysis.py +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import math + +def tem_curve(data): + '''温度曲线绘制''' + hour = list(data['小时']) + tem = list(data['温度']) + for i in range(0, 24): + if math.isnan(tem[i]) == True: + tem[i] = tem[i - 1] + tem_ave = sum(tem) / 24 # 求平均温度 + tem_max = max(tem) + tem_max_hour = hour[tem.index(tem_max)] # 求最高温度 + tem_min = min(tem) + tem_min_hour = hour[tem.index(tem_min)] # 求最低温度 + x = [] + y = [] + for i in range(0, 24): + x.append(i) + y.append(tem[hour.index(i)]) + plt.figure(1) + plt.plot(x, y, color='red', label='温度') # 画出温度曲线 + plt.scatter(x, y, color='red') # 点出每个时刻的温度点 + plt.plot([0, 24], [tem_ave, tem_ave], c='blue', linestyle='--', label='平均温度') # 画出平均温度虚线 + plt.text(tem_max_hour + 0.15, tem_max + 0.15, str(tem_max), ha='center', va='bottom', fontsize=10.5) # 标出最高温度 + plt.text(tem_min_hour + 0.15, tem_min + 0.15, str(tem_min), ha='center', va='bottom', fontsize=10.5) # 标出最低温度 + plt.xticks(x) + plt.legend() + plt.title('一天温度变化曲线图') + plt.xlabel('时间/h') + plt.ylabel('摄氏度/℃') + plt.show() + +def hum_curve(data): + """相对湿度曲线绘制""" + hour = list(data['小时']) + hum = list(data['相对湿度']) + for i in range(0, 24): + if math.isnan(hum[i]) == True: + hum[i] = hum[i - 1] + hum_ave = sum(hum) / 24 # 求平均相对湿度 + hum_max = max(hum) + hum_max_hour = hour[hum.index(hum_max)] # 求最高相对湿度 + hum_min = min(hum) + hum_min_hour = hour[hum.index(hum_min)] # 求最低相对湿度 + x = [] + y = [] + for i in range(0, 24): + x.append(i) + y.append(hum[hour.index(i)]) + plt.figure(2) + plt.plot(x, y, color='blue', label='相对湿度') # 画出相对湿度曲线 + plt.scatter(x, y, color='blue') # 点出每个时刻的相对湿度 + plt.plot([0, 24], [hum_ave, hum_ave], c='red', linestyle='--', label='平均相对湿度') # 画出平均相对湿度虚线 + plt.text(hum_max_hour + 0.15, hum_max + 0.15, str(hum_max), ha='center', va='bottom', fontsize=10.5) # 标出最高相对湿度 + plt.text(hum_min_hour + 0.15, hum_min + 0.15, str(hum_min), ha='center', va='bottom', fontsize=10.5) # 标出最低相对湿度 + plt.xticks(x) + plt.legend() + plt.title('一天相对湿度变化曲线图') + plt.xlabel('时间/h') + plt.ylabel('百分比/%') + plt.show() + +def air_curve(data): + """空气质量曲线绘制""" + hour = list(data['小时']) + air = list(data['空气质量']) + print(type(air[0])) + for i in range(0, 24): + if math.isnan(air[i]) == True: + air[i] = air[i - 1] + air_ave = sum(air) / 24 # 求平均空气质量 + air_max = max(air) + air_max_hour = hour[air.index(air_max)] # 求最高空气质量 + air_min = min(air) + air_min_hour = hour[air.index(air_min)] # 求最低空气质量 + x = [] + y = [] + for i in range(0, 24): + x.append(i) + y.append(air[hour.index(i)]) + plt.figure(3) + + for i in range(0, 24): + if y[i] <= 50: + plt.bar(x[i], y[i], color='lightgreen', width=0.7) # 1等级 + elif y[i] <= 100: + plt.bar(x[i], y[i], color='wheat', width=0.7) # 2等级 + elif y[i] <= 150: + plt.bar(x[i], y[i], color='orange', width=0.7) # 3等级 + elif y[i] <= 200: + plt.bar(x[i], y[i], color='orangered', width=0.7) # 4等级 + elif y[i] <= 300: + plt.bar(x[i], y[i], color='darkviolet', width=0.7) # 5等级 + elif y[i] > 300: + plt.bar(x[i], y[i], color='maroon', width=0.7) # 6等级 + plt.plot([0, 24], [air_ave, air_ave], c='black', linestyle='--') # 画出平均空气质量虚线 + plt.text(air_max_hour + 0.15, air_max + 0.15, str(air_max), ha='center', va='bottom', fontsize=10.5) # 标出最高空气质量 + plt.text(air_min_hour + 0.15, air_min + 0.15, str(air_min), ha='center', va='bottom', fontsize=10.5) # 标出最低空气质量 + plt.xticks(x) + plt.title('一天空气质量变化曲线图') + plt.xlabel('时间/h') + plt.ylabel('空气质量指数AQI') + plt.show() + +def wind_radar(data): + """风向雷达图""" + wind = list(data['风力方向']) + wind_speed = list(data['风级']) + for i in range(0, 24): + if wind[i] == "北风": + wind[i] = 90 + elif wind[i] == "南风": + wind[i] = 270 + elif wind[i] == "西风": + wind[i] = 180 + elif wind[i] == "东风": + wind[i] = 360 + elif wind[i] == "东北风": + wind[i] = 45 + elif wind[i] == "西北风": + wind[i] = 135 + elif wind[i] == "西南风": + wind[i] = 225 + elif wind[i] == "东南风": + wind[i] = 315 + degs = np.arange(45, 361, 45) + temp = [] + for deg in degs: + speed = [] + # 获取 wind_deg 在指定范围的风速平均值数据 + for i in range(0, 24): + if wind[i] == deg: + speed.append(wind_speed[i]) + if len(speed) == 0: + temp.append(0) + else: + temp.append(sum(speed) / len(speed)) + print(temp) + N = 8 + theta = np.arange(0. + np.pi / 8, 2 * np.pi + np.pi / 8, 2 * np.pi / 8) + # 数据极径 + radii = np.array(temp) + # 绘制极区图坐标系 + plt.axes(polar=True) + # 定义每个扇区的RGB值（R,G,B），x越大，对应的颜色越接近蓝色 + colors = [(1 - x / max(temp), 1 - x / max(temp), 0.6) for x in radii] + plt.bar(theta, radii, width=(2 * np.pi / N), bottom=0.0, color=colors) + plt.title('一天风级图', x=0.2, fontsize=20) + plt.show() + +def calc_corr(a, b): + """计算相关系数""" + a_avg = sum(a) / len(a) + b_avg = sum(b) / len(b) + cov_ab = sum([(x - a_avg) * (y - b_avg) for x, y in zip(a, b)]) + sq = math.sqrt(sum([(x - a_avg) ** 2 for x in a]) * sum([(x - b_avg) ** 2 for x in b])) + corr_factor = cov_ab / sq + return corr_factor + +def corr_tem_hum(data): + """温湿度相关性分析""" + tem = data['温度'] + hum = data['相对湿度'] + plt.scatter(tem, hum, color='blue') + plt.title("温湿度相关性分析图") + plt.xlabel("温度/℃") + plt.ylabel("相对湿度/%") + plt.text(20, 40, "相关系数为：" + str(calc_corr(tem, hum)), fontdict={ 'size': '10', 'color': 'red'}) + plt.show() + print("相关系数为：" + str(calc_corr(tem, hum))) + +def main(): + plt.rcParams['font.sans-serif'] = ['SimHei'] # 解决中文显示问题 + plt.rcParams['axes.unicode_minus'] = False # 解决负号显示问题 + data1 = pd.read_csv('weather1.csv', encoding='gb2312') + print(data1) + tem_curve(data1) + hum_curve(data1) + air_curve(data1) + wind_radar(data1) + corr_tem_hum(data1) + +if __name__ == '__main__': + main() \ No newline at end of file