pyecharts 画K线记录 精细版

import pandas as pd
from pyecharts import options as opts
from pyecharts.charts import Kline, Line, Bar, Grid, EffectScatter
from pyecharts.globals import SymbolType
from pyecharts.commons.utils import JsCode


def drawKline(df):
    # kline
    x = df.index.tolist()
    y = list(df.loc[:, ['o', 'c', 'l', 'h']].round(2).values)
    y = [i.tolist() for i in y]  # 里面的单个数组也必须转换成list
    # kline = Kline(init_opts=opts.InitOpts(width="100%", height="800px"), )
    kline = Kline()
    kline.add_xaxis(x)
    kline.add_yaxis("kline", y)
    kline.set_global_opts(
        yaxis_opts=opts.AxisOpts(is_scale=True, splitline_opts=opts.SplitLineOpts(is_show=True)),
        # tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross",is_show_content=False),
        datazoom_opts=[
            opts.DataZoomOpts(is_show=False, type_="inside", xaxis_index=[0, 0], range_end=50),
            # xaxis_index=[0, 0]设置第一幅图为内部缩放
            opts.DataZoomOpts(is_show=False, xaxis_index=[0, 1], pos_top="97%", range_end=50),
            # xaxis_index=[0, 1]连接第二幅图的axis
        ],

    )
    # line
    ma5 = df['c'].rolling(5).mean()
    ma10 = df['c'].rolling(10).mean()
    ma20 = df['c'].rolling(20).mean()
    line = Line()
    line.add_xaxis(x)
    line.add_yaxis('MA5', ma5.round(2).tolist(), is_smooth=True)
    line.add_yaxis('MA10', ma10.round(2).tolist(), is_smooth=True)
    line.add_yaxis('MA20', ma20.round(2).tolist(), is_smooth=True)
    line.set_series_opts(label_opts=opts.LabelOpts(is_show=False))  # 是否显示数据标签
    # KD PD KK PK
    es = EffectScatter()
    # KD
    v1 = df.index[df['KD'] == 1].tolist()
    v2 = df['l'].loc[v1].tolist()
    es.add_xaxis(v1)
    es.add_yaxis('KD', v2, symbol=SymbolType.ARROW)
    # PD
    v1 = df.index[df['PD'] == 1].tolist()
    v2 = df['h'].loc[v1].tolist()
    es.add_xaxis(v1)
    es.add_yaxis('PD', v2, symbol=SymbolType.ARROW, symbol_rotate=180)
    # Kk
    v1 = df.index[df['KK'] == 1].tolist()
    v2 = (df['h'].loc[v1] * 1.01).tolist()  # 向上偏移1% 防止重叠看不清
    es.add_xaxis(v1)
    es.add_yaxis('KK', v2, symbol=SymbolType.TRIANGLE, symbol_rotate=180)
    # pk
    v1 = df.index[df['PK'] == 1].tolist()
    v2 = (df['l'].loc[v1] * 0.99).tolist()  # 向下偏移1% 防止重叠看不清
    es.add_xaxis(v1)
    es.add_yaxis('PK', v2, symbol=SymbolType.TRIANGLE)
    es.set_series_opts(label_opts=opts.LabelOpts(is_show=False))  # 是否显示数据标签
    # overlap
    # kline.overlap(line)
    kline.overlap(es)
    return kline


def drawMACD(df):
    MACD = get_macd(df['c'], 12, 26, 9)

    x = df.index.tolist()
    bar_2 = Bar()
    bar_2.add_xaxis(x)
    bar_2.add_yaxis(
        series_name="MACD",
        y_axis=MACD.MACD.round(2).tolist(),
        label_opts=opts.LabelOpts(is_show=False),
        xaxis_index=1,  # 用于合并显示时排列位置，单独显示不要添加
        yaxis_index=1,  # 用于合并显示时排列位置，单独显示不要添加
        itemstyle_opts=opts.ItemStyleOpts(
            color=JsCode(
                """
                function(params) {
                    var colorList;
                    if (params.data >= 0) {
                      colorList = '#ef232a';
                    } else {
                      colorList = '#14b143';
                    }
                    return colorList;
                }
                """
            ))
    )
    bar_2.set_global_opts(
        xaxis_opts=opts.AxisOpts(
            grid_index=1,  # 用于合并显示时排列位置，单独显示不要添加
            axislabel_opts=opts.LabelOpts(is_show=False),
        ),
        yaxis_opts=opts.AxisOpts(
            grid_index=1,  # 用于合并显示时排列位置，单独显示不要添加
            split_number=4,
        ),
        legend_opts=opts.LegendOpts(is_show=False),
    )
    line_2 = Line()
    line_2.add_xaxis(x)
    line_2.add_yaxis(
        series_name="DIF",
        y_axis=MACD.DIF.round(2),
        xaxis_index=1,
        yaxis_index=2,
        label_opts=opts.LabelOpts(is_show=False),
    )
    line_2.add_yaxis(
        series_name="DEA",
        y_axis=MACD.DEA.round(2),
        xaxis_index=1,
        yaxis_index=2,
        label_opts=opts.LabelOpts(is_show=False),
    )
    line_2.set_global_opts(legend_opts=opts.LegendOpts(is_show=False))
    return bar_2.overlap(line_2)


def drawAll(df):
    df.index = df.index.strftime('%Y-%m-%d %H:%M:%S')
    kline = drawKline(df)
    MACD = drawMACD(df)

    grid_chart = Grid(init_opts=opts.InitOpts(width="100%", height="800px"))
    grid_chart.add(
        kline,
        grid_opts=opts.GridOpts(pos_left="3%", pos_right="1%", height="70%"),
    )
    grid_chart.add(
        MACD,
        grid_opts=opts.GridOpts(
            pos_left="3%", pos_right="1%", pos_top="80%", height="20%"
        )
    )
    grid_chart.render('123.html')


def get_macd(price, fast, slow, smooth):
    exp1 = price.ewm(span=fast, adjust=False).mean()
    exp2 = price.ewm(span=slow, adjust=False).mean()
    DIF = exp1 - exp2
    DEA = DIF.ewm(span=smooth, adjust=False).mean()
    MACD = (DIF - DEA) * 2

    columns1 = pd.DataFrame(DIF).rename(columns={'c': 'DIF'})
    columns2 = pd.DataFrame(DEA).rename(columns={'c': 'DEA'})
    columns3 = pd.DataFrame(MACD).rename(columns={'c': 'MACD'})
    frames = [columns1, columns2, columns3]
    df = pd.concat(frames, join='inner', axis=1)
    return df