Python||五城P.M.2.5数据分析与可视化_使用复式柱状图分析各个城市的P.M.2.5月度差异情况（中）

目录

4.上海市空气质量月度差异

5.沈阳市空气质量月度差异

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五城P.M.2.5数据分析与可视化_使用复式柱状图分析各个城市的P.M.2.5月度差异情况

4.上海市空气质量月度差异

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

#读入文件
sh = pd.read_csv('./Shanghai.csv')
fig = plt.figure(dpi=100,figsize=(10,5))
def PM(grade,str2,str3):
    grade_dist = grade.loc[:, [str2, str3]]
    grade_dist1 = grade_dist.dropna(axis=0, subset=[str3])
    grade_dist_pm = grade.loc[:, [str3]]
    grade_dist1_pm = grade_dist_pm.dropna(axis=0, subset=[str3])
    grade_dist_pm_mean = float(grade_dist1_pm.mean())
    grade_dist_pm_std = float(grade_dist1_pm.std())
    pm_area = grade_dist1[np.abs(grade_dist1[str3] - grade_dist_pm_mean) <= 3 * grade_dist_pm_std]
    grade_dist2 = pm_area.groupby([str2]).mean().reset_index()
    return grade_dist2

def good(pm):
    #优
    degree = pm-35
    for i in range(len(degree)):
        if degree[i] > 0:
            degree[i] = 35
        else:
            degree[i] += 35
    return degree
def moderate(pm):
    #良
    degree = pm-35
    for i in range(len(degree)):
        if degree[i] < 0:
            degree[i] = 0
    degree -= 40
    for i in range(len(degree)):
        if degree[i] > 0:
            degree[i] = 40