在Python中绘制来自数据框的烛台数据

Question

我想从使用熊猫从雅虎下载的数据创建每日烛台图。我无法弄清楚在这种情况下如何使用烛台matplotlib函数。 下面是代码：

#The following example, downloads stock data from Yahoo and plots it. 
from pandas.io.data import get_data_yahoo 
import matplotlib.pyplot as plt 

from matplotlib.pyplot import subplots, draw 
from matplotlib.finance import candlestick 

symbol = "GOOG" 

data = get_data_yahoo(symbol, start = '2013-9-01', end = '2013-10-23')[['Open','Close','High','Low','Volume']] 

ax = subplots() 

candlestick(ax,data['Open'],data['High'],data['Low'],data['Close']) 

感谢

安德鲁。

Answer 1

发现这个问题时，我也正在寻找如何使用烛台与从DataReader服务之一返回的熊猫数据框，如get_data_yahoo。我终于明白了。其中一个关键是另一个问题，由Wes McKinney和RJRyV回答。这里是链接：

Pandas convert dataframe to array of tuples

的关键是阅读candlestick.py函数的定义，以确定它是如何预计接收数据。需要首先转换日期，然后需要将整个数据帧转换为元组数组。

这是我工作的最终代码。也许还有一些其他的烛台图表可以直接用于从股票报价服务返回的熊猫数据框。那肯定很不错。

# Imports 
from pandas.io.data import get_data_yahoo 
from datetime import datetime, timedelta 
import matplotlib.dates as mdates 
from matplotlib.pyplot import subplots, draw 
from matplotlib.finance import candlestick 
import matplotlib.pyplot as plt 

# get the data on a symbol (gets last 1 year) 
symbol = "TSLA" 
data = get_data_yahoo(symbol, datetime.now() - timedelta(days=365)) 

# drop the date index from the dateframe 
data.reset_index(inplace = True) 

# convert the datetime64 column in the dataframe to 'float days' 
data.Date = mdates.date2num(data.Date) 

# make an array of tuples in the specific order needed 
dataAr = [tuple(x) for x in data[['Date', 'Open', 'Close', 'High', 'Low']].to_records(index=False)] 

# construct and show the plot 
fig = plt.figure() 
ax1 = plt.subplot(1,1,1) 
candlestick(ax1, dataAr) 
plt.show() 

Answer 2

我偶然发现了一个很棒的pastebin条目：http://pastebin.com/ne7Fjdiq这样做很好。我也无法正确地调用调用语法。它通常围绕以简单的方式转换数据来使功能正常工作。我的问题是与日期时间。我的格式数据中必须有一些东西。一旦我用范围（maxdata）替换了Date系列，那么它就起作用了。

data = pandas.read_csv('data.csv', parse_dates={'Timestamp': ['Date', 'Time']}, index_col='Timestamp') 
ticks = data.ix[:, ['Price', 'Volume']] 
bars = ticks.Price.resample('1min', how='ohlc') 
barsa = bars.fillna(method='ffill') 
fig = plt.figure() 
fig.subplots_adjust(bottom=0.1) 
ax = fig.add_subplot(111) 
plt.title("Candlestick chart") 
volume = ticks.Volume.resample('1min', how='sum') 
value = ticks.prod(axis=1).resample('1min', how='sum') 
vwap = value/volume 
Date = range(len(barsa)) 
#Date = matplotlib.dates.date2num(barsa.index)# 
DOCHLV = zip(Date , barsa.open, barsa.close, barsa.high, barsa.low, volume) 
matplotlib.finance.candlestick(ax, DOCHLV, width=0.6, colorup='g', colordown='r', alpha=1.0) 
plt.show() 

Answer 3

我没有信誉评论@兰德尔 - 古德温的答案，但对大熊猫0.16.2线：

# convert the datetime64 column in the dataframe to 'float days' 
data.Date = mdates.date2num(data.Date) 

必须是：

data.Date = mdates.date2num(data.Date.dt.to_pydatetime()) 

因为matplotlib不支持numpy datetime64 dtype

Answer 4

这里是解决方案：

from pandas.io.data import get_data_yahoo 
import matplotlib.pyplot as plt 
from matplotlib import dates as mdates 
from matplotlib import ticker as mticker 
from matplotlib.finance import candlestick_ohlc 
import datetime as dt 
symbol = "GOOG" 

data = get_data_yahoo(symbol, start = '2014-9-01', end = '2015-10-23') 
data.reset_index(inplace=True) 
data['Date']=mdates.date2num(data['Date'].astype(dt.date)) 
fig = plt.figure() 
ax1 = plt.subplot2grid((1,1),(0,0)) 
plt.ylabel('Price') 
ax1.xaxis.set_major_locator(mticker.MaxNLocator(6)) 
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d')) 

candlestick_ohlc(ax1,data.values,width=0.2) 

Answer 5

使用背景虚化：

import io 
from math import pi 
import pandas as pd 
from bokeh.plotting import figure, show, output_file 

df = pd.read_csv(
    io.BytesIO(
     b'''Date,Open,High,Low,Close 
2016-06-01,69.6,70.2,69.44,69.76 
2016-06-02,70.0,70.15,69.45,69.54 
2016-06-03,69.51,70.48,68.62,68.91 
2016-06-04,69.51,70.48,68.62,68.91 
2016-06-05,69.51,70.48,68.62,68.91 
2016-06-06,70.49,71.44,69.84,70.11 
2016-06-07,70.11,70.11,68.0,68.35''' 
    ) 
) 

df["Date"] = pd.to_datetime(df["Date"]) 

inc = df.Close > df.Open 
dec = df.Open > df.Close 
w = 12*60*60*1000 

TOOLS = "pan,wheel_zoom,box_zoom,reset,save" 

p = figure(x_axis_type="datetime", tools=TOOLS, plot_width=1000, title 
= "Candlestick") 
p.xaxis.major_label_orientation = pi/4 
p.grid.grid_line_alpha=0.3 

p.segment(df.Date, df.High, df.Date, df.Low, color="black") 
p.vbar(df.Date[inc], w, df.Open[inc], df.Close[inc], fill_color="#D5E1DD", line_color="black") 
p.vbar(df.Date[dec], w, df.Open[dec], df.Close[dec], fill_color="#F2583E", line_color="black") 

output_file("candlestick.html", title="candlestick.py example") 

show(p) 

以上代码从这里分叉： http://bokeh.pydata.org/en/latest/docs/gallery/candlestick.html