前言

最近发现一个功能强大的绘图工具库cufflinks，其最吸引我的地方是内置了量化金融绘图模块，可以很方便地绘制K线和技术指标图表。但遗憾的是，在网络上并没有找到cufflinks的参考手册。虽然网络上有一些介绍cufflinks的博客文章，但都没有详细介绍量化绘图模块的使用方法。

因此本蒟蒻参照cufflinks的github源码，对cufflinks量化金融绘图模块的使用方法做出简要的介绍，希望对您有些许帮助。

cufflinks介绍

cufflinks是对Python绘图库plotly的进一步封装，是基于jupyter notebook的交互式绘图工具，可以很方便地绘制各种交互式图表，布局优美，效果炫酷，操作方便，可以和pandas的数据类型无缝衔接。

cufflinks的量化金融绘图模块接收的金融交易数据为，dataframe格式，index为datetime类型，各列为open、high、low、close、volume，如下：

使用方法

注意：目前cufflinks只能在jupyter notebook中使用，在其他的IDE中使用可能会无法 编译执行。

因为本蒟蒻水平有限，如有错误，欢迎批评指正。

笔者的环境：cufflinks 0.17.3、Python3.7 、Jupyter Notebook

更多信息可以参考cufflinks的源码

安装cufflinks：

pip install cufflinks

1.绘制基础K线（蜡烛）图

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
df=cf.datagen.ohlcv()#cufflinks提供的数据，也可以更改为自定义数据
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.iplot()

效果图:

2.添加趋势线

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_trendline('2015-01-01','2015-04-10',on='close',text='趋势线',textangle=0)#画趋势线，textangle设置文字角度
qf.iplot(up_color='red',down_color='green')

效果图：

参数介绍（摘自源码注释）：

""" Parameters: date0 : string Trendline starting date date1 : string Trendline end date on : string Indicate the data series in which the trendline should be based. 'close' 'high' 'low' 'open' text : string If passed, then an annotation will be added to the trendline (at mid point) kwargs: from_strfmt : string Defines the date formating in which date0 and date1 are stated. default: '%d%b%y' to_strfmt : string Defines the date formatting to which it should be converted. This should match the same format as the timeseries index. default : '%Y-%m-%d' """

3.添加支撑线

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_support('2015-01-12',on='close',mode='toend',text='这是支持线')
qf.iplot()

参数介绍：

""" Parameters: date0 : string The support line will be drawn at the 'y' level value that corresponds to this date. on : string Indicate the data series in which the support line should be based. 'close' 'high' 'low' 'open' mode : string Defines how the support/resistance will be drawn 'starttoened' : (x0,x1) 'fromstart' : (x0,date) 'toend' : (date,x1) text : string If passed, then an annotation will be added to the support line (at mid point) kwargs: from_strfmt : string Defines the date formating in which date0 and date1 are stated. default: '%d%b%y' to_strfmt : string Defines the date formatting to which it should be converted. This should match the same format as the timeseries index. default : '%Y-%m-%d' """

4.添加压力线

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_resistance('2015-01-12',on='close',mode='fromstart',text='这是压力线',textangle=30)
qf.iplot()

效果图：
参数介绍：
与支撑线相似

5.添加注解

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_annotations({'2015-02-01':'我是注解'},fontcolor='red',fontsize=18,textangle=0)
qf.iplot()

效果图：

""" Parameters: annotations : dict or list(dict,) Annotations can be on the form form of {'date' : 'text'} and the text will automatically be placed at the right level on the chart or A Plotly fully defined annotation kwargs : fontcolor : str Text color for annotations fontsize : int Text size for annotations textangle : int Textt angle See https://plot.ly/python/reference/#layout-annotations for a complete list of valid parameters. """

6.添加交易量

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_volume()
qf.iplot(up_color='red',down_color='green')#可以设置主题颜色

效果图：

参数介绍：

""" Parameters: colorchange : bool If True then each volume bar will have a fill color depending on if 'base' had a positive or negative change compared to the previous value If False then each volume bar will have a fill color depending on if the volume data itself had a positive or negative change compared to the previous value column :string Defines the data column name that contains the volume data. Default: 'volume' name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs : base : string Defines the column which will define the positive/negative changes (if colorchange=True). Default = 'close' up_color : string Color for positive bars down_color : string Color for negative bars """

7.添加异同移动平均线MACD

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_macd()
qf.iplot()

效果图：

参数介绍：

""" Parameters: fast_period : int MACD Fast Period slow_period : int MACD Slow Period signal_period : int MACD Signal Period column :string Defines the data column name that contains the data over which the study will be applied. Default: 'close' name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one All formatting values available on iplot() """

8.添加简单移动均线SMA

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_sma(periods=[10,30],color=['red','blue'])
qf.iplot()

参数介绍：

""" Parameters: periods : int or list(int) Number of periods column :string Defines the data column name that contains the data over which the study will be applied. Default: 'close' name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one All formatting values available on iplot() """

9.添加EMA

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_ema(periods=[10,20])
qf.iplot()

效果图：

参数介绍：

""" Parameters: periods : int or list(int) Number of periods column :string Defines the data column name that contains the data over which the study will be applied. Default: 'close' name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one All formatting values available on iplot() """

10.添加RSI

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_rsi(periods=10)
qf.iplot()

效果图：

参数介绍：

""" Parameters: periods : int or list(int) Number of periods rsi_upper : int bounds [0,100] Upper (overbought) level rsi_lower : int bounds [0,100] Lower (oversold) level showbands : boolean If True, then the rsi_upper and rsi_lower levels are displayed column :string Defines the data column name that contains the data over which the study will be applied. Default: 'close' name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one All formatting values available on iplot() """

11.添加布林线

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_bollinger_bands(periods=10)
qf.iplot()

效果图：

参数介绍：

""" Parameters: periods : int or list(int) Number of periods boll_std : int Number of standard deviations for the bollinger upper and lower bands fill : boolean If True, then the innner area of the bands will filled column :string Defines the data column name that contains the data over which the study will be applied. Default: 'close' name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one fillcolor : string Color to be used for the fill color. Example: 'rgba(62, 111, 176, .4)' All formatting values available on iplot() """

12.添加顺势指标/商品通道指标CCI

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_cci(periods=[10,20])
qf.iplot()

效果图：

参数介绍：

""" Parameters: periods : int or list(int) Number of periods cci_upper : int Upper bands level default : 100 cci_lower : int Lower band level default : -100 showbands : boolean If True, then the cci_upper and cci_lower levels are displayed name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one All formatting values available on iplot() """

13.添加平均趋向指数ADX

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_adx(periods=5)
qf.iplot()

效果图：

参数介绍：

""" Parameters: periods : int or list(int) Number of periods name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one All formatting values available on iplot() """

14.添加均幅指标ATR

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_atr(periods=5)
qf.iplot()

效果图：

参数介绍：

""" Parameters: periods : int or list(int) Number of periods name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one All formatting values available on iplot() """

15.添加趋向指标DMI

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_dmi(periods=5)
qf.iplot()

效果图：

参数介绍：

""" Parameters: periods : int or list(int) Number of periods name : string Name given to the study str : string Label factory for studies The following wildcards can be used: {name} : Name of the column {study} : Name of the study {period} : Period used Examples: 'study: {study} - period: {period}' kwargs: legendgroup : bool If true, all legend items are grouped into a single one All formatting values available on iplot() """

拓展内容

1.剔除非交易日期

当我们使用自己的数据绘图时，其默认会把 非交易日也包含在图中。例如下面从tushare中获取数据：

import cufflinks as cf
import tushare as ts
cf.set_config_file(offline=True, world_readable=True)
df=ts.get_hist_data('000001',start='2020-04-15',end='2020-05-13')
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.iplot()

效果图：

可以看到，绘制的图像包含了非交易日。如果我们想要剔除这些非交易日，需要把代码修改为：

import cufflinks as cf
import tushare as ts
cf.set_config_file(offline=True, world_readable=True)
df=ts.get_hist_data('000001',start='2020-04-15',end='2020-05-13')
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
layout = dict(
    xaxis=dict(
        categoryorder="category ascending",#筛除非交易日
        type='category')
)
qf.iplot(layout=layout)

效果图：

可以看到，在添加了layout后，图像底部多出了一个选择横坐标范围的小条。同时在layout中将xaxis的type设置为‘category’便可以剔除非交易日了。

2.抛物转向指标add_ptps报错

除了上面介绍的方法外，cufflinks还有添加抛物转向指标add_ptps(),但我测试的时候，该方法一直报错。

import cufflinks as cf
cf.set_config_file(offline=True, world_readable=True)
df=cf.datagen.ohlcv()
qf=cf.QuantFig(df,title='cufflinks金融绘图样例',legend='top',name='QF')
qf.add_ptps()
qf.iplot()

错误最终指向：

提示说是计算过程中出现了None。
初步考察，应该是cufflinks的源码的问题(如果不是还请大佬指出）
打开cufflinks中的ta.py文件

可以看到，在286行，其将某一单元的初值设置为None，而该单元恰好是在报错的位置出现的变量。
解决方法：注释掉286行。