# -*- coding: utf-8 -*-
import time
from urllib.parse import urlencode
import pandas as pd
import requests
from matplotlib import pyplot as plt
plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False #用来正常显示负号
def gen_secid(rawcode: str)-> str:
'''
生成东方财富专用的secid
Parameters
----------
rawcode : 6 位股票代码
Return
------
str: 指定格式的字符串
'''
# 沪市指数
if rawcode[:3] == '000':
return f'1.{rawcode}'
# 深证指数
if rawcode[:3] == '399':
return f'0.{rawcode}'
# 沪市股票
if rawcode[0] != '6':
return f'0.{rawcode}'
# 深市股票
return f'1.{rawcode}'
def get_k_history(code: str, beg: str, end: str, klt: int = 101, fqt: int = 1)-> pd.DataFrame:
'''
功能获取k线数据
-
参数
code : 6 位股票代码
beg: 开始日期 例如 20200101
end: 结束日期 例如 20200201
klt: k线间距 默认为 101 即日k
klt:1 1 分钟
klt:5 5 分钟
klt:101 日
klt:102 周
fqt: 复权方式
不复权 : 0
前复权 : 1
后复权 : 2
'''
EastmoneyKlines = {
'f51': '日期',
'f52': '开盘',
'f53': '收盘',
'f54': '最高',
'f55': '最低',
'f56': '成交量',
'f57': '成交额',
'f58': '振幅',
'f59': '涨跌幅',
'f60': '涨跌额',
'f61': '换手率'
}
EastmoneyHeaders = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.110 Safari/537.36',
'Accept': '*/*',
'Accept-Language': 'zh-CN,zh;q=0.8,zh-TW;q=0.7,zh-HK;q=0.5,en-US;q=0.3,en;q=0.2',
'Referer': 'http://quote.eastmoney.com/center/gridlist.html',
}
fields = list(EastmoneyKlines.keys())
columns = list(EastmoneyKlines.values())
fields2 = ",".join(fields)
secid = gen_secid(code)
params = (
('fields1', 'f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13'),
('fields2', fields2),
('beg', beg),
('end', end),
('rtntype', '6'),
('secid', secid),
('klt', f'{klt}'),
('fqt', f'{fqt}'),
)
params = dict(params)
# print(params)
base_url = 'https://push2his.eastmoney.com/api/qt/stock/kline/get'
url = base_url + '?' + urlencode(params)
# print(url)
# data = requests.get(url)
# print(data)
json_response: dict = requests.get(
url.replace('%2C',','), headers=EastmoneyHeaders).json()
time.sleep(3)
# print(json_response)
data = json_response.get('data')
# print(data)
if data is None:
if secid[0] == '0':
secid = f'1.{code}'
else:
secid = f'0.{code}'
params['secid'] = secid
url = base_url + '?' + urlencode(params)
json_response: dict = requests.get(
url.replace('%2C',','), headers=EastmoneyHeaders).json()
data = json_response.get('data')
time.sleep(2)
if data is None:
print('股票代码:', code, '可能有误')
return pd.DataFrame(columns=columns)
klines = data['klines']
# klines = data['trends2']
rows = []
for _kline in klines:
kline = _kline.split(',')
rows.append(kline)
df = pd.DataFrame(rows, columns=columns)
return df
if __name__ == "__main__":
# 股票代码
code_dic = {'平煤股份':'601666'}
code, = code_dic.values()
name,= code_dic
# 开始日期
start_date = '20230301'
# 结束日期
end_date = '20230612'
print(f'正在获取 {name} 从 {start_date} 到 {end_date} 的 k线数据......')
# 根据股票代码、开始日期、结束日期获取指定股票代码指定日期区间的k线数据
df = get_k_history(code, start_date, end_date)
# 保存k线数据到表格里面
df.to_csv(f'{name}.csv', encoding='utf-8-sig', index=None)
print(f'股票代码：{code} 的 k线数据已保存到代码目录下的 {name}.csv 文件中')
# print(df['日期'])
plt.figure(figsize=(50,8),dpi=80)
plt.xlabel("日期",fontdict={'fontsize':16})
plt.ylabel(f"股票{name}收盘价格",fontdict={'fontsize':16})
plt.title(f"股票{name}收盘价格走势图",fontdict={'fontsize':20})
x = df['日期']
y = [float(y) for y in df['收盘']]
# print(df.shape)
for x1,y1 in zip(x,y):
plt.text(x1,y1,str(y1),ha='center', va='bottom', fontsize=10)
plt.plot(x,y,'blue',marker='D', markersize=3, label="趋势")
# 换手率
turnover_rate = [float(turnover_rate) for turnover_rate in df['换手率']]
for x2,y2 in zip(x,turnover_rate):
plt.text(x2,y2,str(y2),ha='center', va='bottom', fontsize=10)
plt.plot(x,turnover_rate,'green',marker='D', markersize=3, label="换手率")
# 对齐X轴的刻度
ax = plt.gca()
# 使用axis.set_xticks固定刻度位置
ax.set_xticks(x[::1])
ax.set_xticklabels(df['日期'], rotation='45', ha='right',fontsize='12')
# 调整整个图片的位置
figure = plt.gcf()
figure.subplots_adjust(left=0.2, bottom=0.2)
# 绘制图例
plt.legend(['收盘价', '换手率'])
plt.grid()
plt.yticks(fontsize=12)
plt.savefig('./{}.svg'.format(name))
# plt.show()
