在Python中绘制数据框中的烛台数据

Question

我想根据使用pandas从雅虎下载的数据创建每日烛台图。在这种情况下，我无法弄清楚如何使用烛台matplotlib函数。 这是代码：

#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'])

谢谢

安德鲁。

Answer 1

使用散景：

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)

上面的代码从这里分叉： http://bokeh.pydata.org/en/latest/docs/gallery/candlestick.html

Answer 2

我对@ randall-goodwin的回答没有声誉，但对于pandas 0.16.2行：

# 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 3

我偶然发现了一个很棒的粘贴条目：http://pastebin.com/ne7Fjdiq这样做很好。我也无法正确获取调用语法。它通常围绕以简单的方式转换数据以使函数正常工作。我的问题是日期时间。我的格式数据中必定存在某些内容。一旦我用范围（maxdata）替换Date系列，那么它就可以了。

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 4

以下是解决方案：

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

当我也在寻找如何使用烛台以及从其中一个DataReader服务（如get_data_yahoo）返回的pandas数据帧时，发现了这个问题。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。这是链接：

Pandas convert dataframe to array of tuples

关键是要读取candlestick.py函数定义以确定它预期接收数据的方式。首先需要转换日期，然后需要将整个数据帧转换为元组数组。

这是最适合我的代码。也许还有一些其他的烛台图表可以直接在其中一个股票报价服务返回的pandas数据框架上运行。那将是非常好的。

# 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()