python matplotlib 绘制布林带

最新推荐文章于 2025-04-23 13:26:01 发布

廷益--飞鸟

最新推荐文章于 2025-04-23 13:26:01 发布

阅读量1.3k

点赞数

CC 4.0 BY-SA版权

分类专栏： python 文章标签： python 开发语言后端

本文链接：https://blog.youkuaiyun.com/weixin_45875105/article/details/107332446

python 专栏收录该内容

121 篇文章

订阅专栏

本文介绍如何使用Python的matplotlib库从CSV文件中读取股票数据，并绘制布林带图表。通过计算移动平均线和标准差，展示了布林带上轨和下轨的绘制过程，适用于股票市场分析。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

python matplotlib 绘制布林带

csv文件下载地址:
链接：https://pan.baidu.com/s/1sDe3h0jBliT5QAWGwNK8kg
提取码：tsdt

"""
    绘制布林带
"""

import numpy as np
import datetime as dt
import matplotlib.pyplot as mp
import matplotlib.dates as md


# 方法-日期转换函数
def dmy2ymd(dmy):
    dmy = str(dmy, encoding='utf-8')
    time = dt.datetime.strptime(dmy, '%d-%m-%Y').date()
    t = time.strftime('%Y-%m-%d')
    return t


# 读取csv文件数据
dates, open_price, max_price, min_price, close_prices, volumes = np.loadtxt(
    r".\aapl.csv",
    delimiter=",",
    usecols=(1, 3, 4, 5, 6, 7),
    unpack=True,
    dtype="M8[D], f8, f8, f8, f8, f8",
    converters={1: dmy2ymd})

print(open_price)

# 设置绘图窗口
mp.figure("Apple K Line", facecolor="lightgray")
mp.title("Apple K Line", fontsize=16)
mp.xlabel("Data", fontsize=14)
mp.ylabel("Price", fontsize=14)

# x坐标（时间轴）轴修改
ax = mp.gca()
# 设置主刻度定位器为周定位器（每周一显示主刻度文本）
ax.xaxis.set_major_locator(md.WeekdayLocator(byweekday=md.MO))
ax.xaxis.set_major_formatter(md.DateFormatter('%Y-%m-%d'))
ax.xaxis.set_minor_locator(md.DayLocator())

mp.tick_params(labelsize=8)
mp.grid(linestyle=":")

# 绘制收盘价
dates = dates.astype(md.datetime.datetime)
mp.plot(dates, close_prices, color="r", linestyle="--", linewidth=2, label="close",
        alpha=0.3)

# 加权卷积 均值
x = np.linspace(-1, 0, 5)
weights = np.exp(x)[::-1]
kernel = weights / weights.sum()
ma_53 = np.convolve(close_prices, kernel, "valid")
mp.plot(dates[4:], ma_53, color="orangered", linewidth=2, label="MA-53")

# 计算标准差
stds = np.zeros_like(ma_53)
for i in range(stds.size):
    stds[i] = close_prices[i:i + 5].std()
stds *= 2

# 计算上下线 并绘制布林带
lowers = ma_53 - stds
uppers = ma_53 + stds
mp.plot(dates[4:], uppers, color="red", linewidth=2, label="Upper")
mp.plot(dates[4:], lowers, color="green", linewidth=2, label="Lower")

mp.fill_between(dates[4:], lowers, uppers, lowers < uppers, color="lightgray", alpha=0.3)

mp.legend()
mp.gcf().autofmt_xdate()
mp.show()