本文介绍了Ploly烛台的定制颜色的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
可以为烛台定义自定义颜色吗?我们希望根据我们自己的业务规则为它们上色,而不是默认应用的递增规则和递减规则。
推荐答案
要直接回答您的初始问题,wrt:
是否可以为烛台定义自定义颜色?
从你到目前为止提供的信息,以及缺乏数据和代码,我只能将你的问题解释为:
如何在打开和关闭之间为不同的烛台大小或范围应用不同的颜色。
这张图为极端的向上和向下移动设置了不同的阈值:
df['change'] = df['AAPL.Close'] - df['AAPL.Open']
df_hi = df[df['change']>1.5]
df_lo = df[df['change']<-0.3]
然后,从不被认为是极端数据的数据中设置跟踪(&q;base";):
fig = go.Figure(go.Candlestick(x=df['Date'],
open=df['AAPL.Open'], high=df['AAPL.High'],
low=df['AAPL.Low'], close=df['AAPL.Close']))
然后添加两个额外的轨迹,以包括被认为是极端的动作:
# set up trace with extreme highs
fig.add_traces(go.Candlestick(x=df_hi['Date'],
open=df_hi['AAPL.Open'], high=df_hi['AAPL.High'],
low=df_hi['AAPL.Low'], close=df_hi['AAPL.Close']))
如果这确实是您要找的颜色,我将提供有关如何设置颜色的进一步解释。使用此设置,您还可以设置图例中不同轨迹的子集。
绘图:
完整代码:
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import pandas as pd
# data
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
df=df.tail(15)
df['change'] = df['AAPL.Close'] - df['AAPL.Open']
df_hi = df[df['change']>1.5]
df_lo = df[df['change']<-0.3]
not_hi = df[df.index.isin(df_hi.index)].index
not_lo = df[df.index.isin(df_lo.index)].index
df = df.drop(not_hi)
df = df.drop(not_lo)
# set up figure with values not high and not low
# include candlestick with rangeselector
fig = go.Figure(go.Candlestick(x=df['Date'],
open=df['AAPL.Open'], high=df['AAPL.High'],
low=df['AAPL.Low'], close=df['AAPL.Close']))
# set up trace with extreme highs
fig.add_traces(go.Candlestick(x=df_hi['Date'],
open=df_hi['AAPL.Open'], high=df_hi['AAPL.High'],
low=df_hi['AAPL.Low'], close=df_hi['AAPL.Close']))
# set up traces with extreme lows
fig.add_traces(go.Candlestick(x=df_lo['Date'],
open=df_lo['AAPL.Open'], high=df_lo['AAPL.High'],
low=df_lo['AAPL.Low'], close=df_lo['AAPL.Close']))
color_hi_fill = 'black'
color_hi_line = 'blue'
color_lo_fill = 'yellow'
color_lo_line = 'purple'
fig.data[1].increasing.fillcolor = color_hi_fill
fig.data[1].increasing.line.color = color_hi_line
fig.data[1].decreasing.fillcolor = 'rgba(0,0,0,0)'
fig.data[1].decreasing.line.color = 'rgba(0,0,0,0)'
fig.data[2].increasing.fillcolor = 'rgba(0,0,0,0)'
fig.data[2].increasing.line.color = 'rgba(0,0,0,0)'
fig.data[2].decreasing.fillcolor = color_lo_fill
fig.data[2].decreasing.line.color = color_lo_line
fig.show()
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