不用matplotlib库

好的，如果不使用matplotlib库，你可以尝试使用其他库来进行绘图，比如Plotly。以下是一个使用Plotly绘制K线图、M日移动平均线和BOLL指标线的示例代码：

import pandas as pd
import plotly.graph_objects as go

# 获取股票数据，假设您有一个名为stock_data的数据框
stock_data = pd.read_csv('stock_data.csv')  # 根据您的实际情况修改文件路径和读取方式

# 设置起始日期和结束日期
start_date = '2022-01-01'
end_date = '2022-12-31'

# 根据日期筛选数据
stock_data = stock_data[(stock_data['Date'] >= start_date) & (stock_data['Date'] <= end_date)]

# 计算M日移动平均线
M = 10  # 假设M为10
stock_data['MA'] = stock_data['Close'].rolling(window=M).mean()

# 计算N日标准差
N = 20  # 假设N为20
stock_data['std'] = stock_data['Close'].rolling(window=N).std()

# 计算BOLL指标线
stock_data['mid'] = stock_data['MA']
stock_data['upper'] = stock_data['mid'] + 2 * stock_data['std']
stock_data['lower'] = stock_data['mid'] - 2 * stock_data['std']

# 绘制K线图和指标线
fig = go.Figure(data=[go.Candlestick(x=stock_data['Date'],
                                    open=stock_data['Open'],
                                    high=stock_data['High'],
                                    low=stock_data['Low'],
                                    close=stock_data['Close'])])

fig.add_trace(go.Scatter(x=stock_data['Date'], y=stock_data['MA'],
                         name='MA', line=dict(color='orange')))

fig.add_trace(go.Scatter(x=stock_data['Date'], y=stock_data['upper'],
                         name='Upper BOLL', line=dict(color='red')))

fig.add_trace(go.Scatter(x=stock_data['Date'], y=stock_data['lower'],
                         name='Lower BOLL', line=dict(color='green')))

fig.update_layout(title='Stock K-line and BOLL Indicator',
                  xaxis_title='Date',
                  yaxis_title='Price')

fig.show()

请注意，上述代码中的数据获取、文件路径和数据处理部分需要根据您的实际情况进行修改。此外，您需要安装plotly库来运行此示例代码。