blocks|key|4145712|text|我找到的最好的解决方案是使用Bokeh。这里有一个相关的问题-+Bokeh,+zoom+only+on+single+axis,+adjust+another+axis+accordingly。一个答案链接了一个gist，它给出了一个设置自动Y缩放的烛台的例子。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4145713|不幸的是，这远不是一个“开箱即用”的解决方案，因为它涉及到编写一个自定义的JavaScript回调。然而，解决方案仍然相当简单。我无法运行gist上的代码，主要是因为Pandas+DataReader的问题。以下是代码的更新版本，它使用了Bokeh提供的示例数据(根据Bokeh+Candlesicks+example)，增加了与TradingView的更多相似性，并解决了我发现的其他一些问题：|4145714|import+pandas+as+pd

from+bokeh.io+import+output_file,+show
from+bokeh.plotting+import+figure
from+bokeh.models+import+CustomJS,+ColumnDataSource
from+bokeh.sampledata.stocks+import+MSFT


def+candlestick_plot(df):
++++fig+=+figure(sizing_mode='stretch_both',
+++++++++++++++++tools="xpan,xwheel_zoom,undo,redo,reset,crosshair,save",
+++++++++++++++++active_drag='xpan',
+++++++++++++++++active_scroll='xwheel_zoom',
+++++++++++++++++x_axis_type='datetime')

++++inc+=+df.close+>+df.open
++++dec+=+~inc

++++fig.segment(df.date[inc],+df.high[inc],+df.date[inc],+df.low[inc],+color="green")
++++fig.segment(df.date[dec],+df.high[dec],+df.date[dec],+df.low[dec],+color="red")
++++width_ms+=+12*60*60*1000+#+half+day+in+ms
++++fig.vbar(df.date[inc],+width_ms,+df.open[inc],+df.close[inc],+color="green")
++++fig.vbar(df.date[dec],+width_ms,+df.open[dec],+df.close[dec],+color="red")

++++source+=+ColumnDataSource({'date':+df.date,+'high':+df.high,+'low':+df.low})
++++callback+=+CustomJS(args={'y_range':+fig.y_range,+'source':+source},+code='''
++++++++clearTimeout(window._autoscale_timeout);

++++++++var+date+=+source.data.date,
++++++++++++low+=+source.data.low,
++++++++++++high+=+source.data.high,
++++++++++++start+=+cb_obj.start,
++++++++++++end+=+cb_obj.end,
++++++++++++min+=+Infinity,
++++++++++++max+=+-Infinity;

++++++++for+(var+i=0;+i+<+date.length;+%2B%2Bi)+{
++++++++++++if+(start+<=+date[i]+&&+date[i]+<=+end)+{
++++++++++++++++max+=+Math.max(high[i],+max);
++++++++++++++++min+=+Math.min(low[i],+min);
++++++++++++}
++++++++}
++++++++var+pad+=+(max+-+min)+*+.05;

++++++++window._autoscale_timeout+=+setTimeout(function()+{
++++++++++++y_range.start+=+min+-+pad;
++++++++++++y_range.end+=+max+%2B+pad;
++++++++});
++++''')

++++fig.x_range.callback+=+callback
++++show(fig)

df+=+pd.DataFrame(MSFT)
df["date"]+=+pd.to_datetime(df["date"])
output_file("candlestick.html")
candlestick_plot(df)|code-block|syntax|javascript|4145715|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/q/45785740/2801913|1|https://gist.github.com/kernc/719918ada11298168efd956afc1a04a8|2|https://bokeh.pydata.org/en/latest/docs/gallery/candlestick.html^0|W|1S|0|2Y|4|1|0|3W|J|2|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@$A|X|B|Y|1|Z]|$A|10|B|11|1|12]]|C|$]]|$1|D|3|E|5|6|7|13|8|@]|9|@$A|14|B|15|1|16]]|C|$]]|$1|F|3|G|5|H|7|17|8|@]|9|@]|C|$I|J]]|$1|K|3|-4|5|6|7|18|8|@]|9|@]|C|$]]]|L|$M|$5|N|O|P|C|$Q|R]]|S|$5|N|O|P|C|$Q|T]]|U|$5|N|O|P|C|$Q|V]]]]

The best solution I have found is to use Bokeh. There is a related question here - <a href="https://stackoverflow.com/q/45785740/2801913">Bokeh, zoom only on single axis, adjust another axis accordingly</a>. One answer links a <a href="https://gist.github.com/kernc/719918ada11298168efd956afc1a04a8" rel="noreferrer">gist</a> which gives an example of setting up candlesticks with automatic Y zoom.

Unfortunately this is far from an 'out of the box' solution as it involves coding a custom JavaScript callback. However, the solution is still fairly simple. I couldn't get the code on the gist to run, mainly due to issues with the Pandas DataReader. Here is an updated version of the code which uses the example data Bokeh provides (as per the Bokeh <a href="https://bokeh.pydata.org/en/latest/docs/gallery/candlestick.html" rel="noreferrer">Candlesicks example</a>), adds more similarities with TradingView and irons out a few other issues I found:

<pre><code>import pandas as pd

from bokeh.io import output_file, show
from bokeh.plotting import figure
from bokeh.models import CustomJS, ColumnDataSource
from bokeh.sampledata.stocks import MSFT


def candlestick_plot(df):
 fig = figure(sizing_mode='stretch_both',
 tools="xpan,xwheel_zoom,undo,redo,reset,crosshair,save",
 active_drag='xpan',
 active_scroll='xwheel_zoom',
 x_axis_type='datetime')

 inc = df.close &gt; df.open
 dec = ~inc

 fig.segment(df.date[inc], df.high[inc], df.date[inc], df.low[inc], color="green")
 fig.segment(df.date[dec], df.high[dec], df.date[dec], df.low[dec], color="red")
 width_ms = 12*60*60*1000 # half day in ms
 fig.vbar(df.date[inc], width_ms, df.open[inc], df.close[inc], color="green")
 fig.vbar(df.date[dec], width_ms, df.open[dec], df.close[dec], color="red")

 source = ColumnDataSource({'date': df.date, 'high': df.high, 'low': df.low})
 callback = CustomJS(args={'y_range': fig.y_range, 'source': source}, code='''
 clearTimeout(window._autoscale_timeout);

 var date = source.data.date,
 low = source.data.low,
 high = source.data.high,
 start = cb_obj.start,
 end = cb_obj.end,
 min = Infinity,
 max = -Infinity;

 for (var i=0; i &lt; date.length; ++i) {
 if (start &lt;= date[i] &amp;&amp; date[i] &lt;= end) {
 max = Math.max(high[i], max);
 min = Math.min(low[i], min);
 }
 }
 var pad = (max - min) * .05;

 window._autoscale_timeout = setTimeout(function() {
 y_range.start = min - pad;
 y_range.end = max + pad;
 });
 ''')

 fig.x_range.callback = callback
 show(fig)

df = pd.DataFrame(MSFT)
df["date"] = pd.to_datetime(df["date"])
output_file("candlestick.html")
candlestick_plot(df)
</code></pre>

blocks|key|4145771|text|我一直在努力让这个点缀式的烛台图以我想要的方式工作，所以我开发了一个代码示例来分享。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4145772|这不依赖于任何额外的javascript或其他库，除了Dash、Plotly和一个名为pytz的日期库。示例代码在更新和x范围滑块时提供对yaxis范围的自动更新。Y轴设置为仅显示图表中具有两个刻度填充的条形图的价格范围。|4145773|这对我来说效果很好，我可以在图表顶部添加任意数量的跟踪覆盖。另外，我可以在本地运行它，而不必使用plotly服务。请参阅此处的gitub+repo：|4145774|https://github.com/gersteing/DashCandlestickCharting/blob/master/README.md|offset|length|4145775|对那些想尝试的人来说。使用Flask在本地运行。享受吧！|4145776|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|0|0|22|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|T|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|U|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|V|8|@]|9|@$H|W|I|X|1|Y]]|A|$]]|$1|J|3|K|5|6|7|Z|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|10|8|@]|9|@]|A|$]]]|M|$N|$5|O|P|Q|A|$R|G]]]]

I struggled with getting the plotly candlestick chart to work the way I wanted to work so I developed a code example to share. 

This does not depend on any additional javascript or other libraries except Dash, Plotly, and a date library called pytz. Example code provides automatic updates to the yaxis range when and x range slider is updated. Y axis is set to show only price range of bars that are in the chart with a two tick padding. 

This worked well for me and I can potentially add any number of trace overlays that I want on top of the chart. Plus, I can run it locally without having to use plotly services. See gitub repo here:

<a href="https://github.com/gersteing/DashCandlestickCharting/blob/master/README.md" rel="nofollow noreferrer">https://github.com/gersteing/DashCandlestickCharting/blob/master/README.md</a>

For whom ever wants to try it out. Runs locally using Flask. Enjoy!

blocks|key|4145795|text|以下是如何在finplot中执行此操作：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4145796|import+yfinance+as+yf
import+finplot+as+fplt

df+=+yf.download('%5ENDX',+start='2018-01-01',+end='2020-04-29')
print(df)
fplt.candlestick_ochl(df[['Open','Close','High','Low']])
fplt.show()|code-block|syntax|javascript|4145797|免责声明:我是作者。Finplot具有自动Y-scaling，使用干净的api快速且自以为是。请参阅示例here。|offset|length|4145798|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/highfestiva/finplot/tree/master/finplot^0|0|0|1G|4|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|T|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|U|8|@]|9|@$I|V|J|W|1|X]]|A|$]]|$1|K|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|L|$M|$5|N|O|P|A|$Q|R]]]]

This is how to do it in finplot:

<pre><code>import yfinance as yf
import finplot as fplt

df = yf.download('^NDX', start='2018-01-01', end='2020-04-29')
print(df)
fplt.candlestick_ochl(df[['Open','Close','High','Low']])
fplt.show()
</code></pre>

Disclaimer: I am the author. Finplot has auto-Y-scaling, is fast and opinionated with a clean api. See examples <a href="https://github.com/highfestiva/finplot/tree/master/finplot" rel="noreferrer">here</a>.

I am looking for a Python plotting library that allows me to plot candlesticks (preferably the OHLC bars variant) with X zoom via mousewheel scrolling (or similar) and an automatically scaled Y axis when zooming.

As an example of what I am looking for, tradingview.com does this perfectly. See <a href="https://uk.tradingview.com/chart/?symbol=NASDAQ:NDX" rel="noreferrer">https://uk.tradingview.com/chart/?symbol=NASDAQ:NDX</a>. OHLC bars can be seen by clicking the candlestick icon near the top left and selecting 'Bars'.

Plotly is almost able to do this. The Ohlc class in plotly.graph_objs give the OHLC bars, and the default rangeslider is a nice feature for X zoom (mousewheel scrolling can also be easily enabled). However automatic Y scaling is not available in Python as far as I can see (<a href="https://stackoverflow.com/questions/50301094/y-axis-autoscaling-with-x-range-sliders-in-plotly">Y-axis autoscaling with x-range sliders in plotly</a>), thus zooming in on a section of data makes it appear flat. Example code - <a href="https://plot.ly/python/ohlc-charts/" rel="noreferrer">https://plot.ly/python/ohlc-charts/</a>

Another option I am familiar with is PyQtGraph, which has nice zoom features but does not have support for candlestick plots. Using this would involve coding my own candlestick object.

There are a wide range of Python plotting libraries out there that I don't know. Is there anything out there that has out of the box support for this? Can anyone provide example code to do this cleanly?

Python: Plot candlesticks with automatic Y zoom

Python

我正在寻找一个Python绘图库，允许我绘制烛台(最好是OHLC条变体)，通过鼠标滚轮滚动(或类似)X缩放，并在缩放时自动缩放Y轴。作为我正在寻找的一个例子，tradingview.com完美地做到了这一点。参见。OHLC条可以通过单击左上角的烛台图标并选择“条”来查看。Plotly几乎能够做到这一点。plotly.g...

问Python:使用自动Y缩放打印烛台
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