python+pyecharts绘制股票k线图与日均收益率图

k线图的绘制

数据库的连接不再赘述，需要的数据为：
1.开盘价格
2.最高价格
3.最低价格
4.收盘价格

源代码：

from pyecharts import options as opts
from pyecharts.charts import Kline
import sqlutil as ql
import datetime

ql.conn.connect()
ql.cursor = ql.conn.cursor(cursor=ql.pymysql.cursors.DictCursor)
sql = 'select date, start_price, max_price, min_price, stop_price from abc001_defect;'
ql.cursor.execute(sql)
ret = ql.cursor.fetchall()
print(ret)

x_data = []
y_data = []

for i in ret:
    str_date = datetime.datetime.strftime(i['date'], '%Y-%m-%d')
    x_data.append(str_date)
    y_data.append([i['start_price'], i['max_price'], i['min_price'], i['stop_price']])

c = (
    Kline(init_opts=opts.InitOpts(width="1440px", height="800px"))
    .add_xaxis(xaxis_data=x_data)
    .add_yaxis(
        "kline",
        y_data,
        itemstyle_opts=opts.ItemStyleOpts(
            color="#ec0000",
            color0="#00da3c",
            border_color="#8A0000",
            border_color0="#008F28",
        ),
    )
    .set_global_opts(
        xaxis_opts=opts.AxisOpts(is_scale=True),
        yaxis_opts=opts.AxisOpts(
            is_scale=True,
            splitarea_opts=opts.SplitAreaOpts(
                is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
            ),
        ),
        datazoom_opts=[opts.DataZoomOpts(type_="inside")],
        title_opts=opts.TitleOpts(title="abc001 K线走势图"),
    )
    .render("abc001kline.html")
)

效果图：

日均收益率图

日均收益率计算方法：

源代码：

import datetime
import sqlutil as ql
import pyecharts.options as opts
from pyecharts.charts import Line
import matplotlib as plt

ql.conn.connect()
ql.cursor = ql.conn.cursor(cursor=ql.pymysql.cursors.DictCursor)
sql = ('''select date, start_price, stop_price from abc001_defect where DATE_FORMAT(date, '%Y-%m-%d') >= '2019-01-01' and DATE_FORMAT(date, '%Y-%m-%d') <= '2019-12-31';''')
ql.cursor.execute(sql)
ret = ql.cursor.fetchall()
print(ret)

price_difference = []
stop_price = []
str_date = []
daliy_rate = ['NONE']

for i in ret:
    str_date.append(datetime.datetime.strftime(i['date'], '%Y-%m-%d'))
    stop_price.append(i['stop_price'])
    price_difference.append(float(format(i['stop_price'] - i['start_price'], '.6f')))
print(str_date)

print(price_difference)
print(stop_price)

# 计算每日收益收益率返回每日收益率list
def fun(differencelist, stoplist, daliylist):
    for i in range(len(differencelist)):
        if i != 0:
            daliylist.append(float(format(differencelist[i - 1] / stoplist[i], '.6f')))
    return daliylist

daliy_rate = fun(price_difference, stop_price, daliy_rate)
print(daliy_rate)

# 年化收益率
sum = 0
for x in range(len(daliy_rate)):
    if x != 0:
        sum = sum + float(daliy_rate[x])
mu = sum / len(daliy_rate)
print(mu)
year_rate = (1 + mu)**len(ret) - 1
print("年化收益率：{}".format(year_rate))

# 日收益率图
x_data = str_date
y_data = daliy_rate
(
    Line()
    .set_global_opts(
        tooltip_opts=opts.TooltipOpts(is_show=False),
        xaxis_opts=opts.AxisOpts(type_="category"),
        yaxis_opts=opts.AxisOpts(
            type_="value",
            axistick_opts=opts.AxisTickOpts(is_show=True),
            splitline_opts=opts.SplitLineOpts(is_show=True),
        ),
    )
    .add_xaxis(xaxis_data=x_data)
    .add_yaxis(
        series_name="",
        y_axis=y_data,
        symbol="emptyCircle",
        is_symbol_show=True,
        is_smooth=True,
        label_opts=opts.LabelOpts(is_show=False),
    )
    .render("abc001rateline.html")
)

效果图：