前言
最近天气异常暴热，看到某些地方地表温度居然达到70°，这就离谱
所以就想采集一下天气的数据，做个可视化图，回忆一下去年的天气情况
- python 3.8 运行代码
- pycharm 2021.2 辅助敲代码
- requests 第三方模块
url = 'https://tianqi.2345.com/Pc/GetHistory?areaInfo%5BareaId%5D=54511&areaInfo%5BareaType%5D=2&date%5Byear%5D=2022&date%5Bmonth%5D=5' response = requests.get(url) print(response)
返回<Response [200]>: 请求成功
print(response.json())
结构化数据解析：Python字典取值
非结构化数据解析：网页结构
json_data = response.json() html_data = json_data['data'] select = parsel.Selector(html_data) trs = select.css('table tr') for tr in trs[1:]: # 网页结构 # html网页 <td>asdfwaefaewfweafwaef</td> <a></a> <div></div> # ::text: 我需要这个 标签里面的文本内容 td = tr.css('td::text').getall() print(td)
with open('天气数据.csv', encoding='utf-8', mode='a', newline='') as f: csv_writer = csv.writer(f) csv_writer.writerow(td)
data = pd.read_csv('天气数据.csv') data
data[['日期','星期']] = data['日期'].str.split(' ',expand=True,n=1) data
data[['最高温度','最低温度']] = data[['最高温度','最低温度']].apply(lambda x: x.str.replace('°','')) data.head()
import matplotlib.pyplot as plt import matplotlib.colors as mcolors import seaborn as sns #设置全局默认字体 为 雅黑 plt.rcParams['font.family'] = ['Microsoft YaHei'] # 设置全局轴标签字典大小 plt.rcParams["axes.labelsize"] = 14 # 设置背景 sns.set_style("darkgrid",{"font.family":['Microsoft YaHei', 'SimHei']}) # 设置画布长宽 和 dpi plt.figure(figsize=(18,8),dpi=100) # 自定义色卡 cmap = mcolors.LinearSegmentedColormap.from_list("n",['#95B359','#D3CF63','#E0991D','#D96161','#A257D0','#7B1216']) # 绘制热力图 ax = sns.heatmap(data_pivot, cmap=cmap, vmax=30, annot=True, # 热力图上显示数值 linewidths=0.5, ) # 将x轴刻度放在最上面 ax.xaxis.set_ticks_position('top') plt.title('北京最近10个月天气分布',fontsize=16) #图片标题文本和字体大小 plt.show()
color0 = ['#FF76A2','#24ACE6'] color_js0 = """new echarts.graphic.LinearGradient(0, 1, 0, 0, [{offset: 0, color: '#FFC0CB'}, {offset: 1, color: '#ed1941'}], false)""" color_js1 = """new echarts.graphic.LinearGradient(0, 1, 0, 0, [{offset: 0, color: '#FFFFFF'}, {offset: 1, color: '#009ad6'}], false)""" tl = Timeline() for i in range(0,len(data_bj)): coordy_high = list(data_bj['最高温度'])[i] coordx = list(data_bj['日期'])[i] coordy_low = list(data_bj['最低温度'])[i] x_max = list(data_bj['日期'])[i]+datetime.timedelta(days=10) y_max = int(max(list(data_bj['最高温度'])[0:i+1]))+3 y_min = int(min(list(data_bj['最低温度'])[0:i+1]))-3 title_date = list(data_bj['日期'])[i].strftime('%Y-%m-%d') c = ( Line( init_opts=opts.InitOpts( theme='dark', #设置动画 animation_opts=opts.AnimationOpts(animation_delay_update=800),#(animation_delay=1000, animation_easing="elasticOut"), #设置宽度、高度 width='1500px', height='900px', ) ) .add_xaxis(list(data_bj['日期'])[0:i]) .add_yaxis( series_name="", y_axis=list(data_bj['最高温度'])[0:i], is_smooth=True,is_symbol_show=False, linestyle_opts={ 'normal': { 'width': 3, 'shadowColor': 'rgba(0, 0, 0, 0.5)', 'shadowBlur': 5, 'shadowOffsetY': 10, 'shadowOffsetX': 10, 'curve': 0.5, 'color': JsCode(color_js0) } }, itemstyle_opts={ "normal": { "color": JsCode( """new echarts.graphic.LinearGradient(0, 0, 0, 1, [{ offset: 0, color: '#ed1941' }, { offset: 1, color: '#009ad6' }], false)""" ), "barBorderRadius": [45, 45, 45, 45], "shadowColor": "rgb(0, 160, 221)", } }, ) .add_yaxis( series_name="", y_axis=list(data_bj['最低温度'])[0:i], is_smooth=True,is_symbol_show=False, # linestyle_opts=opts.LineStyleOpts(color=color0[1],width=3), itemstyle_opts=opts.ItemStyleOpts(color=JsCode(color_js1)), linestyle_opts={ 'normal': { 'width': 3, 'shadowColor': 'rgba(0, 0, 0, 0.5)', 'shadowBlur': 5, 'shadowOffsetY': 10, 'shadowOffsetX': 10, 'curve': 0.5, 'color': JsCode(color_js1) } }, ) .set_global_opts( title_opts=opts.TitleOpts("北京2021年每日最高最低温度变化\n\n{}".format(title_date),pos_left=330,padding=[30,20]), xaxis_opts=opts.AxisOpts(type_="time",max_=x_max),#, interval=10,min_=i-5,split_number=20,axistick_opts=opts.AxisTickOpts(length=2500),axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color="grey")) yaxis_opts=opts.AxisOpts(min_=y_min,max_=y_max),#坐标轴颜色,axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color="grey")) ) ) tl.add(c, "{}".format(list(data_bj['日期'])[i])) tl.add_schema( axis_type='time', play_interval=100, # 表示播放的速度 pos_bottom="-29px", is_loop_play=False, # 是否循环播放 width="780px", pos_left='30px', is_auto_play=True, # 是否自动播放。 is_timeline_show=False) tl.render_notebook()
# 背景色 background_color_js = ( "new echarts.graphic.LinearGradient(0, 0, 0, 1, " "[{offset: 0, color: '#c86589'}, {offset: 1, color: '#06a7ff'}], false)" ) # 线条样式 linestyle_dic = { 'normal': { 'width': 4, 'shadowColor': '#696969', 'shadowBlur': 10, 'shadowOffsetY': 10, 'shadowOffsetX': 10, } } timeline = Timeline(init_opts=opts.InitOpts(bg_color=JsCode(background_color_js), width='980px',height='600px')) bj, gz, sh, sz= [], [], [], [] all_max = [] x_data = data_10[data_10['城市'] == '北京']['日'].tolist() for d_time in range(len(x_data)): bj.append(data_10[(data_10['日'] == x_data[d_time]) & (data_10['城市']=='北京')]["最高温度"].values.tolist()[0]) gz.append(data_10[(data_10['日'] == x_data[d_time]) & (data_10['城市']=='广州')]["最高温度"].values.tolist()[0]) sh.append(data_10[(data_10['日'] == x_data[d_time]) & (data_10['城市']=='上海')]["最高温度"].values.tolist()[0]) sz.append(data_10[(data_10['日'] == x_data[d_time]) & (data_10['城市']=='深圳')]["最高温度"].values.tolist()[0]) line = ( Line(init_opts=opts.InitOpts(bg_color=JsCode(background_color_js), width='980px',height='600px')) .add_xaxis( x_data, ) .add_yaxis( '北京', bj, symbol_size=5, is_smooth=True, is_hover_animation=True, label_opts=opts.LabelOpts(is_show=False), ) .add_yaxis( '广州', gz, symbol_size=5, is_smooth=True, is_hover_animation=True, label_opts=opts.LabelOpts(is_show=False), ) .add_yaxis( '上海', sh, symbol_size=5, is_smooth=True, is_hover_animation=True, label_opts=opts.LabelOpts(is_show=False), ) .add_yaxis( '深圳', sz, symbol_size=5, is_smooth=True, is_hover_animation=True, label_opts=opts.LabelOpts(is_show=False), ) .set_series_opts(linestyle_opts=linestyle_dic) .set_global_opts( title_opts=opts.TitleOpts( title='北上广深10月份最高气温变化趋势', pos_left='center', pos_top='2%', title_textstyle_opts=opts.TextStyleOpts(color='#DC143C', font_size=20)), tooltip_opts=opts.TooltipOpts( trigger="axis", axis_pointer_type="cross", background_color="rgba(245, 245, 245, 0.8)", border_width=1, border_color="#ccc", textstyle_opts=opts.TextStyleOpts(color="#000"), ), xaxis_opts=opts.AxisOpts( # axislabel_opts=opts.LabelOpts(font_size=14, color='red'), # axisline_opts=opts.AxisLineOpts(is_show=True, # linestyle_opts=opts.LineStyleOpts(width=2, color='#DB7093')) is_show = False ), yaxis_opts=opts.AxisOpts( name='最高气温', is_scale=True, # min_= int(min([gz[d_time],sh[d_time],sz[d_time],bj[d_time]])) - 10, max_= int(max([gz[d_time],sh[d_time],sz[d_time],bj[d_time]])) + 10, name_textstyle_opts=opts.TextStyleOpts(font_size=16,font_weight='bold',color='#5470c6'), axislabel_opts=opts.LabelOpts(font_size=13,color='#5470c6'), splitline_opts=opts.SplitLineOpts(is_show=True, linestyle_opts=opts.LineStyleOpts(type_='dashed')), axisline_opts=opts.AxisLineOpts(is_show=True, linestyle_opts=opts.LineStyleOpts(width=2, color='#5470c6')) ), legend_opts=opts.LegendOpts(is_show=True, pos_right='1%', pos_top='2%', legend_icon='roundRect',orient = 'vertical'), )) timeline.add(line, '{}'.format(x_data[d_time])) timeline.add_schema( play_interval=1000, # 轮播速度 is_timeline_show=True, # 是否显示 timeline 组件 is_auto_play=True, # 是否自动播放 pos_left="0", pos_right="0" ) timeline.render_notebook()
本站文章如无特殊说明，均为本站原创，如若转载，请注明出处：近段时间天气暴热，所以采集北上广深去年天气数据，制作可视化图看下 - Python技术站
微信扫一扫 
支付宝扫一扫 