十分钟用 Python 绘制动态排行图 —— 以 A 股历年市值前十股票排行榜为例

import requests
params = params = {
    "isPagination": "true",
    "searchDate": "2021-01-11"
}

headers = {
    "Referer": "http://www.sse.com.cn/market/stockdata/marketvalue/",
    "Accept-Encoding": "gzip, deflate",
    "Connection": "keep-alive",
    "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36"
}

url="http://query.sse.com.cn/marketdata/tradedata/queryTopMktValByPage.do"

response = requests.get(url, headers = headers, params = params)

print(response.text)

# 接上
import re
text = response.text
result = re.search('"result":\[(.*?)\]', text).group(1)
temp = {}
stock_info = re.findall('"market":"(.*?)",.*?"productA":"(.*?)",.*?"productName":"(.*?)",.*?"rank":(.*?)\}', result, re.DOTALL)


f = open(file_path + '/stock_history_market_value.csv', 'a+', newline = '')
print('正在写入:', trade_date)
writer = csv.DictWriter(f, ['year', 'trade_date', 'code', 'stock_name', 'market_value', 'rank'])

for info in stock_info:
    temp = {
        "year": 2021,
        "trade_date": "2021-01-11",
        "code": info[1],
        "stock_name": info[2],
        "market_value": info[0],
        "rank": info[3]
    }
    print(temp)
    writer.writerow(temp)
print('已完成', trade_date)

def get_monthly_market_value(year):
# 如果参数是本年，则取本月前每个月取最后一天的市值排名，本月则取脚本时间的前一天的市值排名
    if year == datetime.date.today().year:
        this_month = datetime.date.today().month
        for month in range(1, this_month+1):
            if month == datetime.date.today().month:
                trade_date = (datetime.date.today() - timedelta(days=1)).strftime('%Y-%m-%d')
                spider_market_value(year, trade_date)
            else:
                trade_date = str(year) + '-' + str(month) + '-' + str(calendar.monthrange(year, month)[1])
                spider_market_value(year, trade_date)
    # 如果参数为历年，则取每个月最后一天的市值排名
    else:
    for month in range(1, 13):        trade_date = str(year) + '-' + str(month) + '-' + str(calendar.monthrange(year, month)[1])
        spider_market_value(year, trade_date)

# 给每一个股票随机一种颜色
random.seed(444)
get_colors = lambda n: list(map(lambda i:"#" +"%06x" % random.randint(0x111111, 0xffffff),range(n)))
colors = get_colors(df['code'].nunique())

codecolors = dict()
uni_code = set(df['code'])
for code, color in zip(uni_code, colors):
codecolors[code] = color


def draw_barchart(trade_date):
    plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']
    plt.rcParams['animation.embed_limit'] = 2**128
    
    # 读取当天的数据
    df_date = df[df['trade_date'] == trade_date]
    df_date = df_date.sort_values(by = ['market_value'], ascending = True)
    
    # 每次绘制前必须先清空画布，不然图像会重叠的
    ax.clear()
    
    # 绘制水平柱状图
   ax.barh(df_date['stock_name'].astype(str), df_date['market_value'], color = [codecolors[c] for c in df_date['code']])
    
    # 标记文案
    dx = df_date['market_value'].max()/200
    for i, (value, code) in enumerate(zip(df_date['market_value'], df_date['stock_name'].astype(str))):
       ax.text(value-dx, i, code, size = 14, weight = 600, ha = 'right', va = 'bottom')
        ax.text(value+dx, i, f'{value:,.0f}', size = 14, ha = 'left', va = 'bottom')
    
    # 标记帧日期
   ax.text(1, 0.45, trade_date.split('-')[0] + '-' + trade_date.split('-')[1], transform = ax.transAxes, color = '#777777', size = 46, ha = 'right')
    
    # 标记轴标签
    ax.text(0, 1.06, "市值（万元）", transform = ax.transAxes, size = 12, color = '#777777')
    
    # 设置 X 轴坐标的位置为顶部
    ax.xaxis.set_ticks_position('top')
    
    #设置 X 轴坐标的颜色和字体大小
    ax.tick_params(axis = 'x', color = '#777777')
    ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
    
    # 设置图形与边框的距离
    ax.margins(0, 0.01)
    ax.grid(which = 'major', axis = 'x', linestyle = '-')
    ax.set_axisbelow(True)
    
    # 设置标题
    ax.text(0.3, 1.05, '历年市值前10股票', transform = ax.transAxes, size = 48, weight = 600, ha = 'left')
    
    # 去掉边框
    plt.box(False)

fig, ax = plt.subplots(figsize=(22, 10))
animator = animation.FuncAnimation(fig, draw_barchart, frames = trade_date_list, interval = 125)
HTML(animator.to_jshtml())