In [14]:

    

# -*- coding: utf-8 -*-

from __future__ import unicode_literals
from __future__ import print_function

from pyecharts import Kline, Bar, Line, Grid, Overlap
import tushare as ts

def kline_js(name, df, prices_cols=None, ma=('ma10',), width=1600, height=750, kline_xaxis_pos='top', render_path=None):
    '''
    @params:
    - name: str                      #图例名称
    - df:  pandas.DataFrame          #columns包含 prices_cols、‘volume’
    - prices_cols : list             #默认 [u'open', u'close', u'low', u'high']
    - ma=('ma10',): list or tuple    #移动平均周期
    - width=1600, height=750         # 默认图片大小
    - kline_xaxis_pos='top'           #k-line图例默认在上方
    - render_path： str               #html file path to save
    '''
    if not prices_cols:
        prices_cols = [u'open', u'close', u'low', u'high']

    if not set(prices_cols+['volume']).issubset(set(df.columns)):
        raise AttributeError("%s or 'volume' not in columns" %
                             str(prices_cols))


    kline = Kline(name, width=width, height=height)
    kline.add('k-candle',
              df.index.format(),
              df[prices_cols].values.tolist(),
              is_datazoom_show=True,
              datazoom_xaxis_index=[0, 1],
              xaxis_pos=kline_xaxis_pos,
              is_xaxislabel_align=True,
              )

    # volume
    if not 'price_change' in df.columns:
        df['price_change'] = df[prices_cols[1]].diff()
    ups = df.where(df.price_change > 0, 0)['volume']
    downs = df.where(~(df.price_change > 0), 0)['volume']

    bar = Bar()
    bar.add('up',
            x_axis=ups.index.format(),
            y_axis=ups.values.tolist(),
            is_datazoom_show=True,
            legend_top="70%",
            is_stack=True,
            is_xaxislabel_align=True,
            )
    bar.add('down',
            x_axis=downs.index.format(),
            y_axis=downs.values.tolist(),
            is_datazoom_show=True,
            is_stack=True,
            legend_top="70%",
            legend_orient='vertical',
            legend_pos='left',
            yaxis_pos='right',
            is_xaxislabel_align=True,
            # mark_line=["average"],
            )
    # add ma
    line = Line()
    for ma_ in ma:
        if ma_ in df.columns:       
            line.add(ma_, df.index.format(), df[ma_].values.tolist())
            #print(df[ma_])
    overlap = Overlap()
    overlap.add(kline)  # overlap kline and ma
    overlap.add(line)
    # merge
    grid1 = Grid()
    grid1.add(overlap, grid_bottom="35%")
    grid1.add(bar, grid_top="60%")



    return grid1  # .render('k-line.html')


    

In [17]:

    

df = ts.get_hist_data('002456', ktype='60')
kline_js('hs300_k-line-5min',
         df,
         ma=('ma5', 'ma10','ma20'),
         width=800, height=800,
         )


    

    
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