数据可视化：CSV格式，JSON格式

from datetime import datetimeimport matplotlib.pyplot as pltimport csvimport numpy as npwith open(‘csv_file\photo.csv‘) as f_obj: ???reader = csv.reader(f_obj) ???dates,heights_1,heights_2 = [],[],[] ???for row in reader: ???????try: ???????????height_1 = float(row[3])#将字符串转换为浮点型 ???????????height_2 = float(row[4]) ???????????# 将字符串‘2018-2-15-13-35-1‘转换为一个表示日期时间的对象 ???????????date = datetime.strptime(row[0], ‘%Y-%m-%d-%H-%M-%S‘) ???????except ValueError: #如果有哪一天的数据缺失，打印缺失日期 ???????????print(date,‘missing data.‘) ???????else: ???????????# 将所有高程插入列表 ???????????dates.append(date) ???????????heights_1.append(height_1) ???????????heights_2.append(height_2)fig = plt.figure(figsize=(12,8))plt.tick_params(axis=‘both‘,labelsize=14)#为防止x轴标签重叠，让日期型的x轴标签自动展现fig.autofmt_xdate(rotation=45)#在同一个窗口中绘制两条折线x = np.array(dates)y = np.array(heights_1)for a,b in zip(x,y): ???#用text()标注,%.nf其中n表示显示小数后面几位，%b表示只标注y ???plt.text(a,b+0.1,‘%.2f‘%b,ha = ‘center‘,va = ‘bottom‘, ???????????fontsize=8) ???#用annotate()标注，xytext表示偏移距离，%b表示只标注y ???#plt.annotate(‘%s‘%b,xy=(a,b),xytext=(-20,10), ????????????????#textcoords=‘offset points‘,fontsize=8)plt.plot(dates,heights_1,linewidth=3,c=‘c‘)x = np.array(dates)y = np.array(heights_2)for a,b in zip(x,y): ???plt.text(a, b + 0.1, ‘%.2f‘ % b, ha=‘center‘, va=‘bottom‘, ????????????fontsize=8)plt.plot(dates,heights_2,linewidth=3,c=‘red‘)#fill_between()接受一个x值系列和两个Y值系列，并填充两个y值系列之间的空间plt.fill_between(dates,heights_1,heights_2,facecolor=‘greenyellow‘, ????????????????alpha=0.3)#alpha值代表颜色透明度，默认1plt.show()

import jsonfrom pygal.style import RotateStyle,LightColorizedStyle#import pygal.maps.worldimport pygal_maps_world.mapsfrom pygal_maps_world.i18n import COUNTRIES#定义一个获取两位国别码的函数def get_country_code(country_name): ???for code,name in COUNTRIES.items(): ???????if name == country_name: ???????????return code ???return Nonefilename = ‘json_file\population_data.json‘with open(filename) as f: ???#将文件中的字典存储到列表中 ???pop_data = json.load(f)#将每个国家2010年的人口数据加入字典cc_populations = {}for pop_dict in pop_data: ???if pop_dict[‘Year‘] == ‘2010‘: ???????country_name = pop_dict["Country Name"] ???????population = int(float(pop_dict[‘Value‘])) ???????code = get_country_code(country_name) ???????if code: ???????????cc_populations[code] = population ???????????#print(code + ‘:‘ + str(population)) ???????else: ???????????print( ‘Error - ‘ + country_name)#将世界人口数量等级分为三组cc_pops_1,cc_pops_2,cc_pops_3 = {},{},{}for cc,pop in cc_populations.items(): ???if pop < 10000000: ???????cc_pops_1[cc] = pop ???elif pop < 1000000000: ???????cc_pops_2[cc] = pop ???else: ???????cc_pops_3[cc] = pop#看看每组有多少个国家print(len(cc_populations),len(cc_pops_1),len(cc_pops_2),len(cc_pops_3))wm_style = RotateStyle(‘#336699‘,base_style=LightColorizedStyle)#wm = pygal.maps.world.World()wm = pygal_maps_world.maps.World(style=wm_style)wm.title = ‘World Population in 2010,by Country‘wm.add(‘0-10m‘,cc_pops_1)wm.add(‘10m-1bn‘,cc_pops_2)wm.add(‘>1bn‘,cc_pops_3)wm.render_to_file(‘images\world_population.svg‘)