如何在 Python 中制作可滚动的烛台图？
how to make srollable candelstick plot in Python?
我有以下烛台图。我想让它滚动，以便我可以看到更多详细信息。当前情节太长，看不到细节。
我在这里找到了使线图可滚动的示例：
但是，更新烛台似乎比更新折线图复杂得多。烛台图 returns 线和补丁。你能帮忙吗？
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 = '2011-9-01', 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.title('How to make it scrollable')
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)
对于你想要的，我建议使用 Plotly，它允许交互式数据可视化（包括滚动、缩放、平移等），并且有一个很好的 Python API。
这里有两种不同的方法（在这两种情况下，您都需要 pip install plotly）
使用 Plotly 网站 API（需要您 create an account here 并获取您的用户名和 API 密钥。您需要连接到互联网才能生成情节。）
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
# Imports for Plotly
import plotly.plotly as py
import plotly.tools as tls
from plotly.tools import FigureFactory as FF
# Put your credentials here
tls.set_credentials_file(username='YourUserName', api_key='YourAPIKey')
# Getting the data
symbol = "GOOG"
data = get_data_yahoo(symbol, start = '2011-9-01', end = '2015-10-23')
data.reset_index(inplace=True)
# Not needed anymore, we'll use the string-formatted dates.
#data['Date']=mdates.date2num(data['Date'].astype(dt.date))
# Creating the Plotly Figure
fig = FF.create_candlestick(data.Open, data.High, data.Low, data.Close, dates=data.Date)
lay = fig.layout
# Formatting the ticks.
lay.xaxis.nticks = 6
lay.xaxis.tickformat = "%Y-%m-%d"
# Removing the hover annotations Plotly adds by default, but this is optional.
lay.hovermode = False
# A nice title...
lay.title = "See, I made it scrollable :)"
py.iplot(fig)
使用 Plotly 的离线模式。我假设您将使用 Jupyter（IPython 笔记本）。您不需要连接到互联网。
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
# Imports for Plotly
from plotly.offline import download_plotlyjs, init_notebook_mode, iplot
import plotly.tools as tls
from plotly.tools import FigureFactory as FF
init_notebook_mode() # Inject Plotly.js into the notebook
# Getting the data
symbol = "GOOG"
data = get_data_yahoo(symbol, start = '2011-9-01', end = '2015-10-23')
data.reset_index(inplace=True)
# Not needed anymore, we'll use the string-formatted dates.
#data['Date']=mdates.date2num(data['Date'].astype(dt.date))
# Creating the Plotly Figure
fig = FF.create_candlestick(data.Open, data.High, data.Low, data.Close, dates=data.Date)
lay = fig.layout
# Formatting the ticks.
lay.xaxis.nticks = 6
lay.xaxis.tickformat = "%Y-%m-%d"
# Removing the hover annotations Plotly adds by default, but this is optional.
lay.hovermode = False
# A nice title...
lay.title = "See, I made it scrollable :)"
iplot(fig)
缩放前的结果...
...在特定区域放大后。
如果您有任何其他问题，请告诉我。希望答案适合您！
您可以绘制整幅图，然后使用滑块小部件修改坐标区。
我无法复制你的数据，因为我没有 pandas.io.data 库，所以我修改了 the candlestick example from here，并添加了滑块。
import matplotlib.pyplot as plt
import datetime
from matplotlib.widgets import Slider
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2004, 2, 1)
date2 = (2004, 4, 12)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc('INTC', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.axis([datetime.date(*date1).toordinal(), datetime.date(*date1).toordinal()+10, 18.5, 22.5])
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
axcolor = 'lightgoldenrodyellow'
axpos = plt.axes([0.2, 0.05, 0.65, 0.03], axisbg=axcolor)
spos = Slider(axpos, 'Position', datetime.date(*date1).toordinal(), datetime.date(*date2).toordinal())
def update(val):
pos = spos.val
ax.axis([pos,pos+10, 18.5, 22.5])
fig.canvas.draw_idle()
spos.on_changed(update)
plt.show()
我硬编码了一些坐标轴大小和位置的值，请在适应您的代码时小心。
如果需要，也可以实现相同的想法来添加垂直滚动。
我有以下烛台图。我想让它滚动，以便我可以看到更多详细信息。当前情节太长，看不到细节。
我在这里找到了使线图可滚动的示例：
但是，更新烛台似乎比更新折线图复杂得多。烛台图 returns 线和补丁。你能帮忙吗？
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 = '2011-9-01', 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.title('How to make it scrollable')
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)
对于你想要的，我建议使用 Plotly，它允许交互式数据可视化（包括滚动、缩放、平移等），并且有一个很好的 Python API。
这里有两种不同的方法（在这两种情况下，您都需要 pip install plotly）
使用 Plotly 网站 API（需要您 create an account here 并获取您的用户名和 API 密钥。您需要连接到互联网才能生成情节。）
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 # Imports for Plotly import plotly.plotly as py import plotly.tools as tls from plotly.tools import FigureFactory as FF # Put your credentials here tls.set_credentials_file(username='YourUserName', api_key='YourAPIKey') # Getting the data symbol = "GOOG" data = get_data_yahoo(symbol, start = '2011-9-01', end = '2015-10-23') data.reset_index(inplace=True) # Not needed anymore, we'll use the string-formatted dates. #data['Date']=mdates.date2num(data['Date'].astype(dt.date)) # Creating the Plotly Figure fig = FF.create_candlestick(data.Open, data.High, data.Low, data.Close, dates=data.Date) lay = fig.layout # Formatting the ticks. lay.xaxis.nticks = 6 lay.xaxis.tickformat = "%Y-%m-%d" # Removing the hover annotations Plotly adds by default, but this is optional. lay.hovermode = False # A nice title... lay.title = "See, I made it scrollable :)" py.iplot(fig)使用 Plotly 的离线模式。我假设您将使用 Jupyter（IPython 笔记本）。您不需要连接到互联网。
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 # Imports for Plotly from plotly.offline import download_plotlyjs, init_notebook_mode, iplot import plotly.tools as tls from plotly.tools import FigureFactory as FF init_notebook_mode() # Inject Plotly.js into the notebook # Getting the data symbol = "GOOG" data = get_data_yahoo(symbol, start = '2011-9-01', end = '2015-10-23') data.reset_index(inplace=True) # Not needed anymore, we'll use the string-formatted dates. #data['Date']=mdates.date2num(data['Date'].astype(dt.date)) # Creating the Plotly Figure fig = FF.create_candlestick(data.Open, data.High, data.Low, data.Close, dates=data.Date) lay = fig.layout # Formatting the ticks. lay.xaxis.nticks = 6 lay.xaxis.tickformat = "%Y-%m-%d" # Removing the hover annotations Plotly adds by default, but this is optional. lay.hovermode = False # A nice title... lay.title = "See, I made it scrollable :)" iplot(fig)
缩放前的结果...
...在特定区域放大后。
如果您有任何其他问题，请告诉我。希望答案适合您！
您可以绘制整幅图，然后使用滑块小部件修改坐标区。
我无法复制你的数据，因为我没有 pandas.io.data 库，所以我修改了 the candlestick example from here，并添加了滑块。
import matplotlib.pyplot as plt
import datetime
from matplotlib.widgets import Slider
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = (2004, 2, 1)
date2 = (2004, 4, 12)
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc('INTC', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)
#plot_day_summary(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.axis([datetime.date(*date1).toordinal(), datetime.date(*date1).toordinal()+10, 18.5, 22.5])
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
axcolor = 'lightgoldenrodyellow'
axpos = plt.axes([0.2, 0.05, 0.65, 0.03], axisbg=axcolor)
spos = Slider(axpos, 'Position', datetime.date(*date1).toordinal(), datetime.date(*date2).toordinal())
def update(val):
pos = spos.val
ax.axis([pos,pos+10, 18.5, 22.5])
fig.canvas.draw_idle()
spos.on_changed(update)
plt.show()
我硬编码了一些坐标轴大小和位置的值，请在适应您的代码时小心。
如果需要，也可以实现相同的想法来添加垂直滚动。