python数据可视化：北上广深空气质量分析

import numpy as np import pandas as pd from pyecharts import Pie, Grid citys = ['beijing', 'shanghai', 'guangzhou', 'shenzhen'] v = [] attrs = [] for i in range(4): filename = 'air_' + citys[i] + '_2018.csv' df = pd.read_csv(filename, header=None, names=["Date", "Quality_grade", "AQI", "AQI_rank", "PM"]) rank_message = df.groupby(['Quality_grade']) rank_com = rank_message['Quality_grade'].agg(['count']) rank_com.reset_index(inplace=True) rank_com_last = rank_com.sort_values('count', ascending=False) attr = rank_com_last['Quality_grade'] attr = np.array(rank_com_last['Quality_grade']) attrs.append(attr) v1 = rank_com_last['count'] v1 = np.array(rank_com_last['count']) v.append(v1) pie1 = Pie("北京", title_pos="28%", title_top="24%") pie1.add("", attrs[0], v[0], radius=[25, 40], center=[30, 27], legend_pos="27%", legend_top="51%", legend_orient="horizontal",) pie2 = Pie("上海", title_pos="58%", title_top="24%") pie2.add("", attrs[1], v[1], radius=[25, 40], center=[60, 27], is_label_show=False, is_legend_show=False) pie3 = Pie("广州", title_pos='28%', title_top='77%') pie3.add("", attrs[2], v[2], radius=[25, 40], center=[30, 80], is_label_show=False, is_legend_show=False) pie4 = Pie("深圳", title_pos='58%', title_top='77%') pie4.add("", attrs[3], v[3], radius=[25, 40], center=[60, 80], is_label_show=False, is_legend_show=False) grid = Grid("2018年北上广深全年空气质量情况", width=1200) grid.add(pie1) grid.add(pie2) grid.add(pie3) grid.add(pie4) grid.render('2018年北上广深全年空气质量情况.html')